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Illinois Institute of Technology

Illinois Institute of Technology. Physics 561 Radiation Biophysics Lecture 8: Fractionation; Carcinogenesis Andrew Howard 26 June 2014. Plans For This Class. Dose fractionation Logic behind it Mathematical models Treatment regimens Radiation Carcinogenesis Animal studies

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Illinois Institute of Technology

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  1. Illinois Institute of Technology Physics 561 Radiation Biophysics Lecture 8:Fractionation; Carcinogenesis Andrew Howard26 June 2014 tumor and normal-tissue responses

  2. Plans For This Class • Dose fractionation • Logic behind it • Mathematical models • Treatment regimens • Radiation Carcinogenesis • Animal studies • Cell-culture studies • Etiology of cancer • Dose-response relationships • Mutagenesis tumor and normal-tissue responses

  3. And now for something mostly different • We’ll move away from nonstochastic late effects to a discussion of treatment modalities for tumors. • Here we’re focusing on the fact that tumors are somewhat DNA repair-deficient and therefore respond differently to ionizing radiation than healthy tissues do • We’ll look, in particular, at dose fractionation as a component of treatment planning for cancer tumor and normal-tissue responses

  4. Fractionation • Radiotherapy can’t wait for research:people need answers now • Even in the 1930’s and 40’s it was recognized that there was an advantage in treating tumors to fractionate the dose, i.e. if the total dose you wanted to deliver was 5 Gy, you got a better therapeutic ratio if you delivered it in several small doses rather than all at once. • We’ll now explore some quantitative models of the relationship between damage and fractionation tumor and normal-tissue responses

  5. Power Law and Timing • Witte:measured dose D required to reach the threshold for skin erythema as a function of dose rate or number of fractions n: • Power law:lnD = a + blnn, i.e.D = ea+blnn = ea eblnn = ea elnnbD = Qnb, where Q = ea. tumor and normal-tissue responses

  6. Power-law treatments, continued • Strandqvist: total time of treatment T:D = UT1-p; 1-p for skin was about 0.2. • Cohen: 1-p is tissue specific (0.30 normal, 0.22 for carcinomas); this enables radiotherapy! Strandqvist modelU=2 Gy1-p = 0.2 tumor and normal-tissue responses

  7. Normalized Standard Dose • Ellis: tolerance dose D for normal tissue is related to the number of fractions Nand the overall treatment time in days, T: • D = rT0.11N0.24 • The value of r is called the Normalized Standard Dose or NSD; it can be determined separately for each tissue and each treatment modality. # of treatments tumor and normal-tissue responses

  8. What are we really doing here? • This is curve-fitting in its most unapologetic form. • As far as I know there is no attempt to attach physical meanings to the exponent (1-p) in the Strandqvist model. • Nor is there a reason to think there’s anything physically significant about the 0.11 and 0.24 exponents in the Ellis formulation tumor and normal-tissue responses

  9. Time of treatment and number of fractions • Clearly time and number of fractions are (anti-)correlated variables • BUT this approach can be helpful in treatment planning, at least within the range of conditions for which the formulas are valid. tumor and normal-tissue responses

  10. Can we do better than this? • Explicit accounting for damage in terms of repairability: • Sublethal • Potentially lethal • Nonrepairable • Model suggests that the limiting slope of lnS vs D as you fractionate a lot is determined by the single-hit (nonrepairable) mechanism tumor and normal-tissue responses

  11. Effect of Fractionation Fig. 11.3: Repair capability;limiting slope determined by fraction sizes < W Radiation Dose Y W X Limiting slope forfraction sizes < W orlow dose rates 0.1 Surviving fraction Effective slope,fraction size X 0.01 Limiting slopefor largedose fraction Effective slope,fraction size Y 0.001 tumor and normal-tissue responses

  12. Douglas & Fowler • Used mouse-foot skin reaction to fractionated doses: ≤ 64 fractions , constant overall time • For an isoeffect, the following equation held: n(aD+bD2) = gwhere n = # of fractions, D = dose per fractionnote: I’m using D where Alpen uses D, to reduce potential confusion with the overall dose. tumor and normal-tissue responses

  13. Douglas-Fowler Assumptions • Repair occurs after single doses • Biological outcome depends on surviving fraction of critical clonogenic cells • Every equal fraction will have same biological effect tumor and normal-tissue responses

  14. Survival fraction,Douglas&Fowler formulation • lnS = n(Fe/a)D • Note that a is not a. • For an appropriate choice of a, Fe = 1/(nD) • Single-dose cell survival is S = exp[(Fe/a)D] • So we do an isoeffect plot of Fe vs. D:Fe = b + cD tumor and normal-tissue responses

  15. Douglas & Fowler Survival Fraction, Continued • Thus lnS = n(bD/a + cD2/a) • cf. Standard LQ model, assuming constant effect per fraction: lnS = -n(aD + bD2) • Defining E = -lnS, E/(nD) = a + bD1/(nD) = a/E + bD/E • plotDvs Fe = 1/(nD)to geta/E, b/E. • In practical situations we may not be able to measure E directly tumor and normal-tissue responses

  16. Fig. 11.4: finding a/E, b/E • a/E = intercept = 1.75 Gy-1 • b/E = slope = 27 Gy-2 • a/b = ratio = 0.0648 Gy 6 4 1/total Dose, Gy-1 2 0.05 0.10 0 0.15 Dose per fraction, Gy tumor and normal-tissue responses

  17. Applicability • We don’t have to be using an LQ model to work with the Douglas-Fowler formulation; we just need a nonzero slope of lnS vs. D at low dose. • Thus MTSH doesn’t work:With MTSH, S= 1 - (1 - exp(-D/D0))n • For n > 1,dS/dD = -n(1-exp(-D/D0))n-1at D = 0, dS/dD = -n(1-e0)n-1= -n(0)n-1 = 0. • For n = 1, S = exp(-D/D0)dS/dD = (-1/D0)exp(-D/D0)at D = 0, dS/dD = (-1/D0)e-0 = -1/D0 ≠ 0. tumor and normal-tissue responses

  18. Withers extension of Fe model • Define flexure dose as the dose per fraction below which no further protection is provided by interfraction repair. • It turns out the flexure dose is a multiple of a/b(units are correct: a/b is in Gy) tumor and normal-tissue responses

  19. Withers extension: results • Let’s pick a reference total dose Dref and a reference dose per fraction Dref. • Then-lnSref= Nref(aDref + bDref2),where Nref is the reference number of doses(Dref= NrefDref) • Then for a different total dose D and different dose per fraction D, D = N D,-lnS= N(aD+ bD2) tumor and normal-tissue responses

  20. Withers result • In order for the reference regimen to have the same effect as the test regimen, • S = Sref, or -lnS = -lnSref • ThereforeNref(aDref + bDref2) = N(aD + bD2), i.e.aNrefDref + bNrefDref2 = aND+ bND2 • But NrefDref = Dref and ND = D, so • NrefDref2 = DrefDref and ND2 = DD • Thus Dref(a+ bDref) = D(a+bD)D/Dref = (a+ bDref)/ (a+bD) = (a/b + Dref)/(a/b+D) tumor and normal-tissue responses

  21. Withers plot (fig. 11.5) Comparison of three different Isoeffect curves, depending on a/b(with ref = 2 Gy): Yellow: α/β=10 GyRed:α/β=3.33 GyBlue: α/β=1.66Gy tumor and normal-tissue responses

  22. Homework for later in July • [This is a variation on problem 1 of chapter 11 in the book. I don't understand the wording of Alpen's problem, so I made up my own version] • Suppose that the Ellis power law equation (11.2) is valid in a particular tissue. A typical tumor dosing regimen consists of twenty treatments over four weeks using weekdays only, i.e. 26 days from the first Monday through the last Friday. Thus if the total dose delivered is 60 Gy, we deliver 3 Gy in each of the 20 treatments. tumor and normal-tissue responses

  23. Homework for later in July, continued • (a) Assuming NSD=17Gy, calculate the tolerance dose associated with this regimen. Will we be able to deliver this treatment regimen without damage to the normal tissue? tumor and normal-tissue responses

  24. Homework, concluded • (b) If we wish to shorten the treatment time to three weeks (19 days from the first Monday to the last Friday) we will have to deliver larger doses per day, e.g. 60/19 = 3.16 Gy/day if we include weekends. If we allow more than one dose delivery per day we can reduce the dose delivered in each treatment back to lower levels, though (1.052 Gy/treatment). Calculate the number of doses we will have to deliver over the 19-day period if we wish to ensure that the full 60 Gy will be tolerated. Determine the dose per treatment. tumor and normal-tissue responses

  25. Reminder about schedules • I will be out of the country from Wednesday 2 July through Wednesday 9 July, so there will be no class on Thursday 3 July or Tuesday 8 July. • I will do a makeup class on Monday 30 June from 10:00am to 12:50pm in Stuart 107 • I will do another makeup class on Friday 11 July from 9:00am to 11:50am in Stuart 213 • If the students who normally attend the live section cannot attend one or both of those makeups, they are welcome to view the videos instead. tumor and normal-tissue responses

  26. Stochastic Effects • These are defined as effects for which the percentage of the population affected by the exposure is dependent on dose • BUT the severity of the [medical] condition in an individual is independent of dose. tumor and normal-tissue responses

  27. Does cancer really work that way? • Not entirely • Fry (1976): • Harderian gland tumors seldom invasive after low doses of low LET radiation • More invasivity and metastasis after higher doses of low LET radiation • Ullrich & Storer (1979):maybe there’s a threshold dose tumor and normal-tissue responses

  28. Is there a threshold at the population level? Measured data Radiation-induced cancer incidence: Cases per 105 people No threshold Threshold model Dose to population tumor and normal-tissue responses

  29. Traditional View of Population Dose-Response Relationships • Notion is that there’s a nonzero slope at D=0, rather than a threshold: Probability of Cancer Incidence Nonzero slope at D=0 Background Incidence Dose tumor and normal-tissue responses

  30. Radiation Carcinogenesis in Animals • Earliest tool in understanding radiation-induced cancer • Consider mice with leukemia brought on by ionizing radiation (fig. 12.1): 50 Corrected for mortality Incidence(% of population) Raw incidence 1 2 3 4 Dose, Gray tumor and normal-tissue responses

  31. The Background Problem • (made-up data): • Error bars make it impossible to figure out which line is correct 3 2 Incidence, % 1 0.2 0.4 0.6 Dose, Gray tumor and normal-tissue responses

  32. In fact, it’s worse! • Substantial error in the dose values too in many cases! 3 2 Incidence, % 1 0.2 0.4 0.6 Dose, Gray tumor and normal-tissue responses

  33. Extrapolation to low dose • The only reliable experimental measurements are made at doses much higher than the levels for which we want to set regulatory limits. Therefore we extrapolate, somehow: Excess Incidence,% of population 4 2 6 Dose, Gray tumor and normal-tissue responses

  34. Differential Sensitivity • Some individuals within a population are more susceptible than others • To tumors • To other conditions • Why? • Defective DNA repair mechanisms • Problems in cell signaling • Lifestyle agents(smoking, drinking, lack of exercise) • Genetic differences among individuals tumor and normal-tissue responses

  35. How does differential sensitivity affect dose-response relationships? Supra-additive Responsesin sensitive populations Additive Response in normal population Tumor incidence Dose tumor and normal-tissue responses

  36. Differential Exposure • Mean dose = 1 Gy • Maximum dose = 10 Gy • Minimum dose = 0 Gy • Mode of dose distribution = 1.2 Gy Fraction receiving given dose 0 1 Dose, Gy tumor and normal-tissue responses

  37. Upton’s Summary of the Animal Data • Neoplasms of almost any type can be induced by irradiation of a suitable animal in a suitable way. • Not every type of neoplasm is increased in frequency by irradiation of animals of one strain. • Carcinogenic effects are interconnected through a variety of mechanisms. • Some mechanisms involve direct effects on the tumor-forming cells; others don’t. • High-LET radiation produces dose-dependent rather than dose-rate-dependent effects tumor and normal-tissue responses

  38. Upton, continued • Development of tumors is multicausal and multistage; effects of radiation may be modified by other agents. • Low to intermediate doses produce no tumors unless promoted by other agents. • At high doses the effect is suppressed by sterilization of potentially transformed cells; this causes saturation. • Time distribution of appearance of tumors varies with type of tumor, genetics and age, conditions of irradiation. • Dose-response curves vary significantly. tumor and normal-tissue responses

  39. Events from transformationto mutated cells (fig. 12.2) • Many factors influence events up through malignancy Radiation event:dose, dose rate, quality Repair Nonproliferating Mutagenic eventsin cell Killing orsterilizingof the cell Oncogenes &Tumor SuppressorGenes ViralActivation Repair Cells with oncogenic mutations tumor and normal-tissue responses

  40. Mutations through Malignancy • Additional influences seen Cells with oncogenic mutations Mitosis HormonesCell Cycle StateProliferative stimuli Other mutations,radiation,and/or chemicals Neoplasia Clonal selectionAltered immune state Malignancy withfull autonomy of growth tumor and normal-tissue responses

  41. Tumors: Definitions • Tumor: abnormal, de-differentiated cellular proliferation • Benign: small mass reaches a certain size and then stops growing • Malignant: those capable of uncontrolled growth & metastasis • Cancer: a malignant tumor • Carcinogen: a chemical or physical agent that increases the likelihood of cancer tumor and normal-tissue responses

  42. Cancer: Prevalence and Significance • 550,000 cancer deaths per year in the US • 20-40% caused by environmental and workplace agents • Others caused by smoking, diet, and natural causes • Teasing apart these statistics is tricky: • Probability of any individual getting cancer under a particular set of circumstances is small • Multistage model makes multiple causes likely tumor and normal-tissue responses

  43. Tumors and Radiation • Stochastic late effects (cf. earlier in this lecture) • Are these effects truly stochastic? • Even with cancer, there exists some dose-response effects in the individual Fig.12.1: myeloid leukemia in mice 60 Adjusted for Intercurrent mortality Incidence,% of population 40 Observed 20 Dose, Gy 4.7 1.5 3.5 tumor and normal-tissue responses

  44. Tumors and Radiation (Cont’d) • Is there a threshold? • Probably not (but is this a red herring?) • Not at the population level • Serious Inquiry: the ED01 experiment Brown & Hoel, Fundamental & Applied Toxicology3: 458 (1983) • More about this in a few slides. Population response Dose tumor and normal-tissue responses

  45. Upton’s rules (remember?) • Irradiation can produce almost any kind of neoplasm if we do it right • Not every type of neoplasm has its incidence increased by irradiation of animals of any one species or strain • Carcinogenic effects depend on a variety of mechanisms • Some effects are direct, some are indirect • Incidence rises more steeply with dose for high-LET radiation than for low-LET radiation • Irradiation interacts with other causative agents • Promotion may depend on other agents tumor and normal-tissue responses

  46. How do Cancers Begin?: The Clonal Theory • In general, mutational events in a single cell are sufficient to begin the process of tumorigenesis • Often several mutations must arise in order for cancer to be a likely outcome • Generally the mutation must be in one of the 50 or so genes that control cell replication and differentiation • The mutagenic events are never enough to guarantee development of cancer(but that still leaves open the possibility that radiation could cause cancer all by itself, if it can act as a promoter too …) • Mutations must be followed by promotional events, which stimulate uncontrolled cell division tumor and normal-tissue responses

  47. Events from transformationto mutated cells (fig. 12.2) • Many factors influence events up through malignancy Radiation event:dose, dose rate, quality Repair Nonproliferating Mutagenic eventsin cell Killing orsterilizingof the cell Oncogenes &Tumor SuppressorGenes ViralActivation Repair Cells with oncogenic mutations tumor and normal-tissue responses

  48. Mutations through Malignancy • Additional influences seen Cells with oncogenic mutations Mitosis HormonesCell Cycle StateProliferative stimuli Other mutations,radiation,and/or chemicals Neoplasia Clonal selectionAltered immune state Malignancy withfull autonomy of growth tumor and normal-tissue responses

  49. Modifying Factors • Immune system  • Hormonal effects • Oncogenes • Oncogenic viruses • Environmental factors tumor and normal-tissue responses

  50. How Cancers Develop: The Multistage Theory • Initiation • DNA damage • e.g. Intercalators • Promotion • Generally not mutational • Involves changes in control systems, e.g. arachidonic acid cascade • Tumors are present and capable of metastasis but haven’t necessarily metastisized • Progression • Development of metastatic tumors tumor and normal-tissue responses

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