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Biomedical subjects

M Zaider

Publications and source records attributed to M Zaider.

At least 19 recordsLinked to original sources
PubMed2000

Postimplantation dosimetric analysis of permanent transperineal prostate implantation: improved dose distributions with an intraoperative computer-optimized conformal planning technique.

PURPOSE: To compare the target coverage and dose to normal tissues after I-125 transperineal permanent implantation (TPI) of the prostate in 90 patients treated with one of three different transperineal techniques. METHODS AND MATERIALS: Detailed postimplant dosimetric evaluations of permanent I-125 implantation procedures were performed on 30 consecutive patients treated between 1995-1996 who underwent TPI using a preplanning CT-based technique, on 30 consecutive patients treated in 1997-1998 who underwent an ultrasound-guided approach with intraoperative determination of seed distribution based on an I-125 nomogram, and on 30 consecutive patients in 1998-1999 who underwent TPI with intraoperative computer-based 3-dimensional conformal optimization. For all three techniques, postimplant CT scans were obtained 4-6 hours after TPI. Dosimetric parameters included V(100), V(90), V(150), D(100), D(90), D(80), as well as maximal and average doses to the urethra and rectal wall. These parameter outcomes are reported as a percentage of the prescription dose. RESULTS: The intraoperative 3D-optimized technique (I-3D) provided superior target coverage with the prescription dose for all dosimetric variables evaluated compared to the other treatment techniques. The median V(100), V(90), and D(90) values for the I-3D technique were 96%, 98%, and 116%, respectively. In contrast, the V(100), V(90), and D(90) values for the CT preplan and ultrasound manual optimization approaches were 86%, 89%, and 88%, respectively and 88%, 92%, and 94%, respectively (I-3D versus other techniques: p < 0.001). The superior target coverage with the I-3D technique was also associated with a higher cumulative implant activity required by the optimization program. A multivariate analysis determined that the treatment technique (I-3D versus other approaches) was an independent predictor of improved target coverage for each parameter analyzed (p < 0.001). In addition, higher cumulative implant activities and smaller prostate target volumes were independent predictors of improved target coverage. The maximum and average urethral doses were significantly lower with the I-3D technique compared to the other techniques; a modest increase in the average rectal dose was also observed with this approach. CONCLUSION: Three-dimensional intraoperative computer optimized TPI consistently provided superior target coverage with the prescription dose and significantly lower urethral doses compared to two other techniques used. These data provide proof-of-principle that improved therapeutic ratios can be achieved with the integration of more sophisticated intraoperative planning for TPI and may potentially have a profound impact on the outcome of patients treated with this modality.

Algorithms↗
PubMed2000

Treatment-plan optimization for soft-tissue sarcoma brachytherapy using a genetic algorithm.

PURPOSE: To describe a treatment-plan optimization system for temporary implant of soft-tissue sarcomas using a genetic algorithm, and evaluate its potential advantages over manual planning. METHODS AND MATERIALS: A planning system that optimizes the distribution of radioactive seeds needed for adequate coverage of the target in the treatment of soft-tissue sarcomas has been designed and implemented. The treatment-planning procedures include simulation, film digitization, target-volume definition, optimized planning, and plan evaluation. The input to the optimization program consists of seed coordinates reconstructed from isocentric films, prescription points, and a list of available seed activities. The optimization is performed using a genetic algorithm. RESULTS: Case studies are presented, which compare plans generated by computer optimization or by trial and error (manually). As expected, computer-optimized plans are often (but not always) superior to manual plans. This is particularly evident for situations where (unavoidably) catheters are far apart or irregularly spaced, in which case the advantages of optimized planning in terms of tumor coverage can be quite dramatic. When the target volume is well contained, the optimized plan minimizes the dose to normal tissue. Computer-based optimization has the additional advantage of being much faster than manual planning; this is valuable because it often reduces the total time the patient will spend in the hospital before implantation. CONCLUSION: Optimized planning with a genetic algorithm and seeds of different activities significantly improves planning efficiency and generally results in improved plan quality. The utility of this optimization system is not limited to sarcoma implants.

Adult↗
PubMed2000

Treatment planning for prostate implants using magnetic-resonance spectroscopy imaging.

PURPOSE: Recent studies have demonstrated that magnetic-resonance spectroscopic imaging (MRSI) of the prostate may effectively distinguish between regions of cancer and normal prostatic epithelium. This diagnostic imaging tool takes advantage of the increased choline plus creatine versus citrate ratio found in malignant compared to normal prostate tissue. The purpose of this study is to describe a novel brachytherapy treatment-planning optimization module using an integer programming technique that will utilize biologic-based optimization. A method is described that registers MRSI to intraoperative-obtained ultrasound images and incorporates this information into a treatment-planning system to achieve dose escalation to intraprostatic tumor deposits. METHODS: MRSI was obtained for a patient with Gleason 7 clinically localized prostate cancer. The ratios of choline plus creatine to citrate for the prostate were analyzed, and regions of high risk for malignant cells were identified. The ratios representing peaks on the MR spectrum were calculated on a spatial grid covering the prostate tissue. A procedure for mapping points of interest from the MRSI to the ultrasound images is described. An integer-programming technique is described as an optimization module to determine optimal seed distribution for permanent interstitial implantation. MRSI data are incorporated into the treatment-planning system to test the feasibility of dose escalation to positive voxels with relative sparing of surrounding normal tissues. The resultant tumor control probability (TCP) is estimated and compared to TCP for standard brachytherapy-planned implantation. RESULTS: The proposed brachytherapy treatment-planning system is able to achieve a minimum dose of 120% of the 144 Gy prescription to the MRS positive voxels using (125)I seeds. The preset dose bounds of 100-150% to the prostate and 100-120% to the urethra were maintained. When compared to a standard plan without MRS-guided optimization, the estimated TCP for the MRS-optimized plan is superior. The enhanced TCP was more pronounced for smaller volumes of intraprostatic tumor deposits compared to estimated TCP values for larger lesions. CONCLUSIONS: Using this brachytherapy-optimization system, we could demonstrate the feasibility of MRS-optimized dose distributions for (125)I permanent prostate implants. Based on probability estimates of anticipated improved TCP, this approach may have an impact on the ability to safely escalate dose and potentially improve outcome for patients with organ-confined but aggressive prostatic cancers. The magnitude of the TCP enhancement, and therefore the risks of ignoring the MR data, appear to be more substantial when the tumor is well localized; however, the gain achievable in TCP may depend quite considerably on the MRS tumor-detection efficiency.

Algorithms↗
PubMed2000

Dosimetric and volumetric criteria for selecting a source activity and a source type ((125)I or (103)Pd) in the presence of irregular seed placement in permanent prostate implants.

PURPOSE: The dosimetric merit of a permanent prostate implant relies on two factors: the quality of the plan itself, and the fidelity of its implementation. The former factor depends on source type and on source strength, while the latter is a combination of skill and experience. The purpose of this study is to offer criteria by which to select a source type ((125)I or (103)Pd) and activity. METHODS AND MATERIALS: Given a prescription dose and potential seed positions along needles, treatment plans were designed for a number of seed types and activities, specifically for (125)I with activities ranging from 0.3 to 0.7 mCi, and for (103)Pd with activities in the range of 0.8 to 1.6 mCi. To avoid human planner bias, an automated computerized planning system based on integer programming was used to obtain optimal seed configurations for each seed type and activity. To simulate the effect of seed-placement inaccuracies, random seed-displacement "errors" were generated for all plans. The displacement errors were assumed to be uniformly distributed within a cube with side equal to 2sigma. The resulting treatment plans were assessed using two volumetric and two dosimetric indices. RESULTS: For (125)I implants a coverage index (CI) of 98.5% or higher can be achieved for all activities (CI is the fraction of the target volume receiving the prescribed or larger dose). The external volume index (EI) (i.e., the amount of healthy tissue, as percentage of the target volume, receiving the prescribed or larger dose) increases from 13.9% to 20% as the activity increases from 0.3 to 0.7 mCi. For implants using (103)Pd, the external volume index increases from 10. 2% to 13.9% whenever CI exceeds 98.5%. Volumetric and dosimetric indices (coverage index, external volume index, D90, and D80) are all sensitive to seed displacement, although the activity dependence of these indices is more pronounced for (125)I than for (103)Pd implants. CONCLUSIONS: For both isotopes, the lower activities studied systematically result in lower EIs. If seeds can be placed within approximately 0.5 cm of their intended position (103)Pd should be preferred because its EI is lower than that of (125)I. For all activities the coverage indices and D90 are within the required range. If seed placement uncertainties are larger than 0.5 cm, (125)I provides slightly better target coverage; however, in terms of external volume (healthy tissue) covered, (103)Pd is superior to (125)I.

Brachytherapy↗
PubMed2000

Tumour control probability: a formulation applicable to any temporal protocol of dose delivery.

An analytic expression for the tumour control probability (TCP), valid for any temporal distribution of dose, is discussed. The TCP model, derived using the theory of birth-and-death stochastic processes, generalizes several results previously obtained. The TCP equation is [equation: see text] where S(t) is the survival probability at time t of the n clonogenic tumour cells initially present (at t = 0), and b and d are, respectively, the birth and death rates of these cells. Equivalently, b = 0.693/Tpot and d/b is the cell loss factor of the tumour. In this expression t refers to any time during or after the treatment; typically, one would take for t the end of the treatment period or the expected remaining life span of the patient. This model, which provides a comprehensive framework for predicting TCP, can be used predictively, or--when clinical data are available for one particular treatment modality (e.g. fractionated radiotherapy)--to obtain TCP-equivalent regimens for other modalities (e.g. low dose-rate treatments).

Brachytherapy↗
PubMed2000

Accuracy in catheter reconstruction in computed tomography planning of high dose rate prostate brachytherapy.

In high dose rate prostate brachytherapy, inadequate reconstruction of catheter geometry in treatment planning may result in erroneous dose delivery. Catheters may be digitized with: (1) Parallel reconstruction: digitized at only one point and assumed parallel and horizontal: (2) Straight reconstruction: digitized at both ends and assumed straight while at an angle: (3) Slice-by-slice reconstruction: digitized on all slices to obtain exact geometry. Our results show that individual catheters are often not parallel to each other, but fairly straight. Parallel reconstruction is the least accurate for dosimetric planning, while slice-by-slice reconstruction is time-consuming. Straight (two-point) reconstruction represents a balance between accuracy and efficiency.

Brachytherapy↗
PubMed1999

Practical considerations in using calculated healthy-tissue complication probabilities for treatment-plan optimization.

PURPOSE: Healthy and neoplastic tissues are generally exposed nonuniformly to ionizing radiation. It is thus useful to develop algorithms that predict the probability of tumor control or normal tissue complication probability (NTCP) for any given spatial pattern of dose delivery. The questions addressed here concern: (a) the sensitivity of the NTCP predictions to the actual model used for extrapolation from uniform irradiation (where some clinical data exist) to nonuniform exposures, (b) its dependence on tissue type, and (c) consequences for treatment-plan optimization. METHODS AND MATERIALS: Two (of several possible) NTCP formulations are used here: the Lyman model and a binomial equation. The effective volume-reduction scheme of Kutcher and Burman is used to obtain the NTCP for an arbitrary distribution of dose. NTCP was calculated for seven organs by postulating a dose distribution of maximum nonuniformity. RESULTS: Both models fit available NTCP data well, but have very different extrapolations for exposures of small tissue volumes and very low values of NTCP (e.g., < 5%) where no data exist. Organs with pronounced volume effects (lung, kidneys) show substantial NTCP differences between the two models. Even in organs where the volume effect is small (e.g., spinal cord, brain), differences in NTCP due to the model selected may still have serious clinical consequences, as an actual example (for the spinal cord) indicates. CONCLUSIONS: NTCP calculations based on extrapolations to volume fractions and/or NTCP levels for which reliable data do not exist depend on the model used to fit the data and the degree of dose nonuniformity. If NTCP is to be used in treatment-plan optimization, the prudent approach is to design plans that reproduce the conditions under which available dose-volume data were taken (e. g., uniform dose distributions).

Algorithms↗
PubMed1999

Treatment planning for brachytherapy: an integer programming model, two computational approaches and experiments with permanent prostate implant planning.

An integer linear programming model is proposed as a framework for optimizing seed placement and dose distribution in brachytherapy treatment planning. The basic model involves using 0/1 indicator variables to describe the placement or non-placement of seeds in a prespecified three-dimensional grid of potential locations. The dose delivered to each point in a discretized representation of the diseased organ and neighbouring healthy tissue can then be modelled as a linear combination of the indicator variables. A system of linear constraints is imposed to attempt to keep the dose level at each point to within specified target bounds. Since it is physically impossible to satisfy all constraints simultaneously, each constraint uses a variable to either record when the target dose level is achieved, or to record the deviation from the desired level. These additional variables are embedded into an objective function to be optimized. Variations on this model are discussed and two computational approaches--a branch-and-bound algorithm and a genetic algorithm--for finding 'optimal' seed placements are described. Results of computational experiments on a collection of prostate cancer cases are reported. The results indicate that both optimization algorithms are capable of producing good solutions within 5 to 15 min, and that small variations in model parameters can have a measurable effect on the dose distribution of the resulting plans.

Algorithms↗
PubMed1998

A little to a lot or a lot to a little: is NTCP always minimized in multiport therapy?

PURPOSE: We address the question of whether or not, for the same average (or integral) dose, a smaller uniform dose to an entire normal tissue structure always results in a lower normal tissue complication probability (NTCP) than does a proportionally larger dose to a partial volume of the same structure. METHODS AND MATERIALS: A recent compilation of NTCP data and two theoretical formulations of the dependence of NTCP on dose and partial volume irradiated-the Lyman probit equation and the binomial model-are used to examine this question. Both models fit equally well available NTCP data. RESULTS: Empirical data indicate that for lung, kidney, and possibly liver (but not for esophagus, brain, or heart), given a fixed tumor dose and fixed integral dose, NTCP can be minimized by irradiating a partial volume fraction rather than the entire normal organ. The binomial model supports this interpretation, whereas the probit model predicts that for all organs uniform irradiation of the whole organ always results in the lowest possible NTCP. CONCLUSIONS: In contrast to what is commonly believed, this study suggests that for at least two normal tissues, namely lung and kidney, there may be situations where "a lot to a little" (i.e., fewer treatment ports) will result in higher tumor control probability and better treatment plan than "a little to a lot" (i.e., multifield treatment). This finding, which is independent of the binomial or probit models used here, depends only on the accuracy of the empirical NTCP data. It is also interesting to note that: a) lung and kidney are commonly classified as parallel tissues, while the others have more of a serial architecture; and b) the choice of the NTCP model can have a profound impact on treatment planning decisions.

Models, Theoretical↗
PubMed1998

Definitions of physical and biological low dose.

The concept of 'low dose' may be understood to refer to an average frequency of microdosimetric events (charged-particle traversals) that is substantially less than unity in cells or their nuclei. An important consequence is that in this case the probability of any effect on autonomous cells must be proportional to the absorbed dose and independent of dose rate. However, this definition may be unnecessarily restrictive because--especially in the case of low-LET radiation--only a small fraction of events may cause the effects under consideration (e.g. cell lethality). This results in larger 'biological' rather than 'physical' 'small doses'. From a pragmatic viewpoint, one may consider the fact that in the linear-quadratic model deviations from proportionality between effect probability and absorbed dose are attributed to a term that depends on the square of the absorbed dose. This permits the selection of a criterion which establishes as 'small doses' those in which such deviations are less than a chosen value which in the examples given here is 10%. Different applications of this criterion to the inactivation of V 79 hamster cells are considered.

Animals↗
PubMed1998

A calculation of the relative biological effectiveness of 125I and 103Pd brachytherapy sources using the concept of proximity function.

The clinical application of encapsulated radioactive sources in brachytherapy plays an important role in the treatment of malignancy. 125I and 103Pd sources have been widely used in the permanent implant of prostate cancer. An important consideration for the choice of brachytherapy sources is their relative biological effectiveness (RBE). Previous calculations of this quantity have used the dose-averaged lineal energy, yD, as a measure of biological effectiveness. In this approach, however, the selection of a relevant site size remains an open question. Here we avoid this problem by using the generalized theory of dual radiation action to calculate the initial slope, alpha, of the dose-effect curves using the proximity function, t(x), and the biological response function, gamma(x). At low doses and/or low dose rates (e.g., prostate implants) the parameter alpha determines the RBE. Proximity function, t(x), is the probability distribution function of distances between pairs of sublesions; and the biological function, gamma(x), is the probability that two sublesions at a distance x apart results in a lesion. Functions t(x) have been calculated for each source using the Monte Carlo transport codes PHOEL and PROTON5. The function gamma(x) has been taken from a published analysis. The RBE values thus obtained are: 1.5 for 125I and 1.6 for 103Pd. The question of whether an "effective" site size exists where yD approximates best the variation of alpha with radiation quality is also addressed.

Brachytherapy↗
PubMed1998

Ab initio electronic structure calculation of a new gene system using the negative factor counting method.

We report a calculation of the electronic structure (density of states and molecular orbitals) of a new gene system-the plasmid shuttle vector pCRR1-performed at the ab initio Hartree-Fock level. To deal with the aperiodicity of the biopolymer, a vectorized version of a negative factor counting (NFC) program has been implemented. With this efficient tool, DNA molecules of up to 100 deoxynucleotides (approximately 10,000 basis functions at the ab initio level) can be calculated routinely. In our calculation the base sequence of the plasmid is explicitly taken into account and a standard helical structure is assumed. Minimum as well as 6-31G basis sets are used in the calculation, and solvation effects are explicitly included. The calculation shows that solvation does not have a significant effect on the electronic structure of the biopolymer. It is found that the frontier orbitals (HOMO and LUMO) are highly localized on the bases. The interpretation of this result in terms of the frontier molecular orbital theory is that the attack of radiation-induced radicals is mainly on the base moieties.

Models, Genetic↗
PubMed1997

Physician/patient-driven risk assignment in radiation oncology: reality or fancy?

PURPOSE: Treatment plan optimization in radiation oncology entails designing multiple x-ray beams to irradiate a tumor to a dose that will achieve locoregional control while minimizing normal tissue complications. For some anatomical sites, it is possible to estimate tumor control probabilities (TCP) and normal tissue complication probabilities (NTCP) as a function of radiation dose. Thus, treatment plan optimization can be based on biologic end points rather than on dose calculations alone. Given multiple plans with different NTCPs and TCPs, a tradeoff must be made between maximizing TCP and maintaining an acceptable NTCP. How do physicians reach these decisions? Can the process be quantified? Should patients participate in the process? METHODS AND MATERIALS: Physicians and patients were asked to rank a series of treatment plans having different combinations of TCP and NTCP. Responses were parametrized into a figure of merit (FM) equation which quantifies predilections of TCP and NTCP. RESULTS: Physician-based FM equations are site- and patient-specific. Variations exist among physicians, but treatment plan selection is often conservative in accordance with the primum non nocere dictum. FM equations generated from the responses of patients suggest that some patients may be willing to accept higher treatment toxicity in exchange for increased TCP. CONCLUSION: The term "optimized treatment plan" contains inherently subjective criteria which reflect one's willingness to accept treatment morbidity in exchange for probability of cure. These criteria may differ among patients and/or physicians. A quantifiable FM may permit the design of custom-made treatment plans that include physician and patient input.

Decision Making↗