Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADAS... more Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is an inherited disorder caused by a mutation in the NOTCH 3 gene, characterized by early onset of subcortical lacunar infarcts in the absence of vascular risk factors and cerebral microbleeds. Homozygosity for the factor Methylenetetrahydrofolate Reductase (MTHFR) is also associated with lacunar stroke risk and cerebral small-vessel disease regardless of the homocysteine level. The coexistence of MTHFR C677T homozygosity and NOTCH 3 mutation has never been reported in the literature previously, and that brings up the challenge of antithrombotic treatment in the presence of cerebral microbleeds.
The maximal duration of cardiopulmonary resuscitation (CPR) is unknown. We report a case of prolo... more The maximal duration of cardiopulmonary resuscitation (CPR) is unknown. We report a case of prolonged CPR. We have then reviewed all published cases with CPR duration equal to or more than 20 minutes. The objective was to determine the survival rate, the neurological outcome, and the characteristics of the survivors.Measurements and Main Results. The CPR data for 82 patients was reviewed. The median duration of CPR was 75 minutes. Patients mean age was 43 ± 21 years with no significant comorbidities. The main causes of the cardiac arrests were myocardial infarction (29%), hypothermia (21%), and pulmonary emboli (12%). 74% of the arrests were witnessed, with a mean latency to CPR of 2 ± 6 minutes and good quality chest compression provided in 96% of the cases. Adjunct therapy included extracorporeal membrane oxygenation (18%), thrombolysis (15.8%), and rewarming for hypothermia (19.5%). 83% were alive at 1 year, with full neurological recovery reported in 63 patients.Conclusion. Pati...
We construct a multi-criteria optimization program that automatically generates the multi-dimensi... more We construct a multi-criteria optimization program that automatically generates the multi-dimensional tradeoff curve of IMRT objectives. Linear convex approximations of non-convex IMRT objectives are used and the Pareto-optimality of approximations in nominal objective space is assessed. Tradeoff solutions are efficiently spread out on the tradeoff curve and an approach for navigating the multi-dimensional curve is shown. The combined effect of column and row generation in speeding up the linear programs is also examined. Our approach is applied to clinical cases and the results examined. An open-source package of our programs, LIRA, is provided.
ABSTRACT Purpose: Dose‐volume histogram (DVH) constraints are frequently used in IMRT planning. F... more ABSTRACT Purpose: Dose‐volume histogram (DVH) constraints are frequently used in IMRT planning. For example, a DVH constraint may state that 5% (but no more) of the voxels in the planning target volume may receive a dose below the prescription level. We want to find out if the percentage of violating voxels can be reduced. We are also interested in the “price” of this reduction of violating voxels, in terms of dose to other voxels and other structures. Methods and Materials: We introduce DVH objectives into IMRT planning. Here the objective is to minimize the number of voxels that violate a given dose constraint. We then integrate DVH objectives into a multi‐criteria optimization (MCO) framework, to analyze the trade offs between DVH objectives and other planning objectives. Relaxation of mixed integer programs (MIPs) used to produce the trade off curve yields a good approximation. This is contrary to relaxation of an MIP with DVH constraints in the conventional framework. A heuristic then fine tunes the relaxation results. Results: Our methods are applied to two clinical cases with both a dose‐volume objective on the tumor and a maximum dose objective on OAR. The trade off curve between those two objectives is calculated in around 20 minutes with the relaxed MIPs compared to 40 hours with the nominal MIPs. The two techniques differ on average by only .77% tumor volume coverage and the heuristic reduces this difference to .35%. Conclusion: The use of DVH objectives (instead of DVH constraints) has the potential to lead to better trade offs in IMRT treatment planning. Surprisingly, DVH objectives simplify the numerical handling of the problem and reduce calculation times.
Could some of the behaviors in Table 1 be (or have been) of utility to the host as well? Note tha... more Could some of the behaviors in Table 1 be (or have been) of utility to the host as well? Note that the behavioral symptoms may not coincide with impaired intellect [Greenebaum and Lurie(1948)]. Furthermore, these symptoms may be vestigial in the sense of having been of utility to the host species at a time when the latter possessed lower intelligence to begin with. It is also important to note that encephalitis is often triggered by physical and emotional stress, so that utility of behaviors is better assessed for such conditions.
The purpose of this study is to calculate Pareto surfaces in multi-criteria radiation treatment p... more The purpose of this study is to calculate Pareto surfaces in multi-criteria radiation treatment planning and to analyse the dependency of the Pareto surfaces on the objective functions used for the volumes of interest. We develop a linear approach that allows us to calculate truly Pareto optimal treatment plans, and we apply it to explore the tradeoff between tumour dose homogeneity and critical structure sparing. We show that for two phantom and two clinical cases, a smooth (as opposed to kinked) Pareto tradeoff curve exists. We find that in the paraspinal cases the Pareto surface is invariant to the response function used on the spinal cord: whether the mean cord dose or the maximum cord dose is used, the Pareto plan database is similar. This is not true for the lung studies, where the choice of objective function on the healthy lung tissue influences the resulting Pareto surface greatly. We conclude that in the special case when the tumour wraps around the organ at risk, e.g. prostate cases and paraspinal cases, the Pareto surface will be largely invariant to the objective function used to model the organ at risk.
Unlike conventional optimization with dose-volume (DV) constraints, multi-criteria optimization (... more Unlike conventional optimization with dose-volume (DV) constraints, multi-criteria optimization (MCO) with DV objectives provides tradeoff information which we believe is necessary for choosing better treatment plans. We show that the MCO formulation with DV objectives is better suited to convex approximation than conventional formulations with DV constraints. We provide a relaxation of the integer programming formulation which reduces the computation time for a single plan from over 5 h to about 2 min, without significantly compromising the results. We also derive a heuristic to improve on the relaxed solutions, adding only a few additional minutes of computation time. We apply these techniques to a skull based tumour case and a paraspinal tumour case. Based on a careful examination of the driving terms in the relaxed formulation and the heuristic, we argue that our techniques should apply more generally for DV objectives in multi-objective IMRT treatment planning.
TU‐C‐T‐6C‐04: Quantifying the Tradeoff Between Complexity and Conformality. [Medical Physics 32, ... more TU‐C‐T‐6C‐04: Quantifying the Tradeoff Between Complexity and Conformality. [Medical Physics 32, 2085 (2005)]. T Bortfeld, D Craft, T Halabi, A Trofimov, M Monz, K Küfer. Abstract. [bold Purpose:] Complex intensity maps in ...
Purpose: To quantify the tradeoff between target dose homogeneity and critical structure sparing ... more Purpose: To quantify the tradeoff between target dose homogeneity and critical structure sparing in two typical IMRT situations (prostate, para‐spinal). Furthermore, to determine the sensitivity to the response model used for critical structures (maximum vs. mean dose). Method and Materials: An EUD‐based multicriteria linear programming environment has been developed. In this work, we enforce a tumor minimum dose and compute solutions which efficiently tradeoff the tumor maximum dose and organ‐at‐risk (OAR) EUD (α⋅max dose+(1 − α) ⋅mean dose). Pareto surfaces resulting from different OAR α values are compared. The technique is applied to the RTOG horseshoe target and circular OAR geometry (varying the OAR's size and location), and to two clinical cases. Results: Mathematically, if the maximum and mean doses of a structure are correlated then the choice of α does not affect the shape of the Pareto frontier. We demonstrate that this correlation is stronger for smaller OARs (a single voxel has a large impact on the mean), and also for symmetrically located OARs, which have a large set of outer ring voxels near the maximum level, as opposed to asymmetrically located OARs where the maximum dose is more localized. As the dose requirements in the tumor get more strict, we see less variance with α, since the feasible solution space is smaller. We consistently see little to no difference between Pareto surfaces for α from 0.5 to 1. Conclusion: By characterizing the conditions under which the Pareto frontier is insensitive to α, we highlight situations where it may not be necessary to know the best value of α, i.e., the exact tissue organization between purely serial and purely parallel. In general we see smooth Pareto surfaces but in some cases there were kinks pointing to outstanding treatment plans.
Purpose: Pelvic lymph nodes are often incorporated en bloc with the prostate as targets in radiat... more Purpose: Pelvic lymph nodes are often incorporated en bloc with the prostate as targets in radiation treatment. It is common practice to realign the fields daily before each treatment to account for prostate motion; however, pelvic nodes are relatively immobile such that adjusting the radiation fields to track the prostate may lead to a geographic miss of the nodes. Here, we explore the magnitude of this problem. Method and Materials: Information from two patients was used in this analysis. IMRT plans were created using the NOMOS/Corvus system and PTVs extending 1.0 cm about the nodes CTV in all directions were planned to 45 Gy in only 25 of the approximately 40 total fractions. Daily field shifts were made by pretreatment ultrasounds of the prostate using the B-mode acquisition and targeting system. Dose of each shift was recalculated using Corvus and the results analyzed using Matlab and CERR. In addition, a random number generator used a clustered probability distribution derived from the total 40 or so shifts to produce alternative scenarios to the 25 shifts. This allowed evaluation of multiple scenarios without need for further timely dose calculation. Results: In all simulations, the cumulative dose over all shifts showed little under-dosage, most of which was at the histogram's tail. For the 90% CTV volume there was a reduction of around 0.7% of prescribed dose. In shifted plans the maximums of each fraction no longer overlap in the same tissue so that most under dosage is expected to be at the histogram's tail. Conclusion: These results suggest that current PTV expansions are adequate to provide prescribed dose coverage of CTVs. It may be possible to further refine PTV expansion definitions to reduce radiation to normal tissues while maintaining treatment delivery to target tissues without causing a geographic miss.
Purpose: Intensity modulated radiation treatment planning for difficult cases is typically a time... more Purpose: Intensity modulated radiation treatment planning for difficult cases is typically a time‐consuming manual search for a plan which gives an acceptable tradeoff between tumor coverage and critical structure sparing. We develop a method to calculate the efficient tradeoff surface of a multi‐objective IMRT inverse planning problem. This serves two purposes: to eliminate the time‐consuming manual search process, and to provide the treatment planners with the complete tradeoff information, allowing them to make more informed decisions. Method and Materials: We formulate a linear multi‐objective IMRTtreatment planning problem, the solution of which is a set of Pareto optimal treatment plans. Since each Pareto optimal plan involves a lengthy optimization, it is prudent to represent the complete surface with as few points as possible. Given the current set of Pareto surface plans, we use geometric considerations to formulate the optimization problem which computes the next plan. In this way, plans are added to the Pareto database until the surface is well represented. Results: The algorithm is applied to two clinical cases. For the prostate case, we display a tradeoff between the prostate coverage, femoral head sparing, and rectal sparing. For the skull‐based tumor, we display a tradeoff between tumor coverage, and the maximum doses of the chiasm, pituitary, and brainstem. Conclusion: We provide a method to efficiently generate Pareto surfaces for treatment planning, even when the number of organs to be traded off exceeds two or three. The method is applicable to any convex objective functions, including equivalent uniform dose, as well as the more standard quadratic penalty IMRT formulations. We expect that the clinical benefit of being able to visualize the tradeoff information — e.g. exactly how a decrease in critical structure dose degrades the tumor coverage — during the planning process will inspire a surge of research in this field.
Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADAS... more Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is an inherited disorder caused by a mutation in the NOTCH 3 gene, characterized by early onset of subcortical lacunar infarcts in the absence of vascular risk factors and cerebral microbleeds. Homozygosity for the factor Methylenetetrahydrofolate Reductase (MTHFR) is also associated with lacunar stroke risk and cerebral small-vessel disease regardless of the homocysteine level. The coexistence of MTHFR C677T homozygosity and NOTCH 3 mutation has never been reported in the literature previously, and that brings up the challenge of antithrombotic treatment in the presence of cerebral microbleeds.
The maximal duration of cardiopulmonary resuscitation (CPR) is unknown. We report a case of prolo... more The maximal duration of cardiopulmonary resuscitation (CPR) is unknown. We report a case of prolonged CPR. We have then reviewed all published cases with CPR duration equal to or more than 20 minutes. The objective was to determine the survival rate, the neurological outcome, and the characteristics of the survivors.Measurements and Main Results. The CPR data for 82 patients was reviewed. The median duration of CPR was 75 minutes. Patients mean age was 43 ± 21 years with no significant comorbidities. The main causes of the cardiac arrests were myocardial infarction (29%), hypothermia (21%), and pulmonary emboli (12%). 74% of the arrests were witnessed, with a mean latency to CPR of 2 ± 6 minutes and good quality chest compression provided in 96% of the cases. Adjunct therapy included extracorporeal membrane oxygenation (18%), thrombolysis (15.8%), and rewarming for hypothermia (19.5%). 83% were alive at 1 year, with full neurological recovery reported in 63 patients.Conclusion. Pati...
We construct a multi-criteria optimization program that automatically generates the multi-dimensi... more We construct a multi-criteria optimization program that automatically generates the multi-dimensional tradeoff curve of IMRT objectives. Linear convex approximations of non-convex IMRT objectives are used and the Pareto-optimality of approximations in nominal objective space is assessed. Tradeoff solutions are efficiently spread out on the tradeoff curve and an approach for navigating the multi-dimensional curve is shown. The combined effect of column and row generation in speeding up the linear programs is also examined. Our approach is applied to clinical cases and the results examined. An open-source package of our programs, LIRA, is provided.
ABSTRACT Purpose: Dose‐volume histogram (DVH) constraints are frequently used in IMRT planning. F... more ABSTRACT Purpose: Dose‐volume histogram (DVH) constraints are frequently used in IMRT planning. For example, a DVH constraint may state that 5% (but no more) of the voxels in the planning target volume may receive a dose below the prescription level. We want to find out if the percentage of violating voxels can be reduced. We are also interested in the “price” of this reduction of violating voxels, in terms of dose to other voxels and other structures. Methods and Materials: We introduce DVH objectives into IMRT planning. Here the objective is to minimize the number of voxels that violate a given dose constraint. We then integrate DVH objectives into a multi‐criteria optimization (MCO) framework, to analyze the trade offs between DVH objectives and other planning objectives. Relaxation of mixed integer programs (MIPs) used to produce the trade off curve yields a good approximation. This is contrary to relaxation of an MIP with DVH constraints in the conventional framework. A heuristic then fine tunes the relaxation results. Results: Our methods are applied to two clinical cases with both a dose‐volume objective on the tumor and a maximum dose objective on OAR. The trade off curve between those two objectives is calculated in around 20 minutes with the relaxed MIPs compared to 40 hours with the nominal MIPs. The two techniques differ on average by only .77% tumor volume coverage and the heuristic reduces this difference to .35%. Conclusion: The use of DVH objectives (instead of DVH constraints) has the potential to lead to better trade offs in IMRT treatment planning. Surprisingly, DVH objectives simplify the numerical handling of the problem and reduce calculation times.
Could some of the behaviors in Table 1 be (or have been) of utility to the host as well? Note tha... more Could some of the behaviors in Table 1 be (or have been) of utility to the host as well? Note that the behavioral symptoms may not coincide with impaired intellect [Greenebaum and Lurie(1948)]. Furthermore, these symptoms may be vestigial in the sense of having been of utility to the host species at a time when the latter possessed lower intelligence to begin with. It is also important to note that encephalitis is often triggered by physical and emotional stress, so that utility of behaviors is better assessed for such conditions.
The purpose of this study is to calculate Pareto surfaces in multi-criteria radiation treatment p... more The purpose of this study is to calculate Pareto surfaces in multi-criteria radiation treatment planning and to analyse the dependency of the Pareto surfaces on the objective functions used for the volumes of interest. We develop a linear approach that allows us to calculate truly Pareto optimal treatment plans, and we apply it to explore the tradeoff between tumour dose homogeneity and critical structure sparing. We show that for two phantom and two clinical cases, a smooth (as opposed to kinked) Pareto tradeoff curve exists. We find that in the paraspinal cases the Pareto surface is invariant to the response function used on the spinal cord: whether the mean cord dose or the maximum cord dose is used, the Pareto plan database is similar. This is not true for the lung studies, where the choice of objective function on the healthy lung tissue influences the resulting Pareto surface greatly. We conclude that in the special case when the tumour wraps around the organ at risk, e.g. prostate cases and paraspinal cases, the Pareto surface will be largely invariant to the objective function used to model the organ at risk.
Unlike conventional optimization with dose-volume (DV) constraints, multi-criteria optimization (... more Unlike conventional optimization with dose-volume (DV) constraints, multi-criteria optimization (MCO) with DV objectives provides tradeoff information which we believe is necessary for choosing better treatment plans. We show that the MCO formulation with DV objectives is better suited to convex approximation than conventional formulations with DV constraints. We provide a relaxation of the integer programming formulation which reduces the computation time for a single plan from over 5 h to about 2 min, without significantly compromising the results. We also derive a heuristic to improve on the relaxed solutions, adding only a few additional minutes of computation time. We apply these techniques to a skull based tumour case and a paraspinal tumour case. Based on a careful examination of the driving terms in the relaxed formulation and the heuristic, we argue that our techniques should apply more generally for DV objectives in multi-objective IMRT treatment planning.
TU‐C‐T‐6C‐04: Quantifying the Tradeoff Between Complexity and Conformality. [Medical Physics 32, ... more TU‐C‐T‐6C‐04: Quantifying the Tradeoff Between Complexity and Conformality. [Medical Physics 32, 2085 (2005)]. T Bortfeld, D Craft, T Halabi, A Trofimov, M Monz, K Küfer. Abstract. [bold Purpose:] Complex intensity maps in ...
Purpose: To quantify the tradeoff between target dose homogeneity and critical structure sparing ... more Purpose: To quantify the tradeoff between target dose homogeneity and critical structure sparing in two typical IMRT situations (prostate, para‐spinal). Furthermore, to determine the sensitivity to the response model used for critical structures (maximum vs. mean dose). Method and Materials: An EUD‐based multicriteria linear programming environment has been developed. In this work, we enforce a tumor minimum dose and compute solutions which efficiently tradeoff the tumor maximum dose and organ‐at‐risk (OAR) EUD (α⋅max dose+(1 − α) ⋅mean dose). Pareto surfaces resulting from different OAR α values are compared. The technique is applied to the RTOG horseshoe target and circular OAR geometry (varying the OAR's size and location), and to two clinical cases. Results: Mathematically, if the maximum and mean doses of a structure are correlated then the choice of α does not affect the shape of the Pareto frontier. We demonstrate that this correlation is stronger for smaller OARs (a single voxel has a large impact on the mean), and also for symmetrically located OARs, which have a large set of outer ring voxels near the maximum level, as opposed to asymmetrically located OARs where the maximum dose is more localized. As the dose requirements in the tumor get more strict, we see less variance with α, since the feasible solution space is smaller. We consistently see little to no difference between Pareto surfaces for α from 0.5 to 1. Conclusion: By characterizing the conditions under which the Pareto frontier is insensitive to α, we highlight situations where it may not be necessary to know the best value of α, i.e., the exact tissue organization between purely serial and purely parallel. In general we see smooth Pareto surfaces but in some cases there were kinks pointing to outstanding treatment plans.
Purpose: Pelvic lymph nodes are often incorporated en bloc with the prostate as targets in radiat... more Purpose: Pelvic lymph nodes are often incorporated en bloc with the prostate as targets in radiation treatment. It is common practice to realign the fields daily before each treatment to account for prostate motion; however, pelvic nodes are relatively immobile such that adjusting the radiation fields to track the prostate may lead to a geographic miss of the nodes. Here, we explore the magnitude of this problem. Method and Materials: Information from two patients was used in this analysis. IMRT plans were created using the NOMOS/Corvus system and PTVs extending 1.0 cm about the nodes CTV in all directions were planned to 45 Gy in only 25 of the approximately 40 total fractions. Daily field shifts were made by pretreatment ultrasounds of the prostate using the B-mode acquisition and targeting system. Dose of each shift was recalculated using Corvus and the results analyzed using Matlab and CERR. In addition, a random number generator used a clustered probability distribution derived from the total 40 or so shifts to produce alternative scenarios to the 25 shifts. This allowed evaluation of multiple scenarios without need for further timely dose calculation. Results: In all simulations, the cumulative dose over all shifts showed little under-dosage, most of which was at the histogram's tail. For the 90% CTV volume there was a reduction of around 0.7% of prescribed dose. In shifted plans the maximums of each fraction no longer overlap in the same tissue so that most under dosage is expected to be at the histogram's tail. Conclusion: These results suggest that current PTV expansions are adequate to provide prescribed dose coverage of CTVs. It may be possible to further refine PTV expansion definitions to reduce radiation to normal tissues while maintaining treatment delivery to target tissues without causing a geographic miss.
Purpose: Intensity modulated radiation treatment planning for difficult cases is typically a time... more Purpose: Intensity modulated radiation treatment planning for difficult cases is typically a time‐consuming manual search for a plan which gives an acceptable tradeoff between tumor coverage and critical structure sparing. We develop a method to calculate the efficient tradeoff surface of a multi‐objective IMRT inverse planning problem. This serves two purposes: to eliminate the time‐consuming manual search process, and to provide the treatment planners with the complete tradeoff information, allowing them to make more informed decisions. Method and Materials: We formulate a linear multi‐objective IMRTtreatment planning problem, the solution of which is a set of Pareto optimal treatment plans. Since each Pareto optimal plan involves a lengthy optimization, it is prudent to represent the complete surface with as few points as possible. Given the current set of Pareto surface plans, we use geometric considerations to formulate the optimization problem which computes the next plan. In this way, plans are added to the Pareto database until the surface is well represented. Results: The algorithm is applied to two clinical cases. For the prostate case, we display a tradeoff between the prostate coverage, femoral head sparing, and rectal sparing. For the skull‐based tumor, we display a tradeoff between tumor coverage, and the maximum doses of the chiasm, pituitary, and brainstem. Conclusion: We provide a method to efficiently generate Pareto surfaces for treatment planning, even when the number of organs to be traded off exceeds two or three. The method is applicable to any convex objective functions, including equivalent uniform dose, as well as the more standard quadratic penalty IMRT formulations. We expect that the clinical benefit of being able to visualize the tradeoff information — e.g. exactly how a decrease in critical structure dose degrades the tumor coverage — during the planning process will inspire a surge of research in this field.
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Papers by Tarek Halabi