RADIOBIOLOIGCALLY BASED TREATMENT PLANNING: THE NEXT FRONTIER. Teddy LaMaster, MS

Transcription

1 RADIOBIOLOIGCALLY BASED TREATMENT PLANNING: THE NEXT FRONTIER Teddy LaMaster, MS

2 RADIOBIOLOGY Radiobiology is the interaction between ionizing radiation and living things. Varies for different cells, organs, organisms. Two types of effects: Stochastic Effects Non-stochastic (deterministic) effects Two types of organ systems Parallel Serial 2

3 STOCHASTIC EFFECTS Thought to have no threshold Probability increases with increased dose If effect occurs the severity is not dependent on dose Example: Patient gets diagnostic x-ray Patient gets radiation induced cancer Severity of radiation induced cancer not correlated with radiation dose from diagnostic x-ray 3

4 DETERMINISTIC EFFECTS Threshold does exist The severity of the effect is dependent on dose Example: Skin Erythema Must meet a threshold dose to get skin erythema Patient s skin erythema will get progressively worse with increased radiation exposure 4

5 TWO TYPES OF ORGAN SYSTEMS Parallel Mean dose dependent Tissue-Volume relationships Serial Maximum dose dependent 5

6 PARALLEL ORGAN WITH A NUMBER OF SUBUNITS 6

7 PARTIAL FUNCTION PRESERVED WHEN THE MAJORITY OF SUBUNITS REMAIN 7

8 SERIAL ORGAN 8

9 FUNCTION DESTROYED BY THE LOSS OF A SINGLE SUBUNIT No Volume Effect Need only Enough Dose to Destroy ONE Functional Subunit 9

10 DOSE-RESPONSE MODELS Linear-Quadratic (LQ) Model TCP Models NTCP Models Generalized Equivalent Uniform Dose (geud) Others Disclosure: Many following slides pulled heavily from TG

11 LINEAR-QUADRATIC (LQ) MODEL Most commonly used to model cell survival Radiation-induced reproductive cell death conclusively linked to DNA damage Specifically double-strand breaks (DSB) 11

12 LINEAR-QUADRATIC FORMULA S represents the fraction of cells surviving irradiation to a dose D in n fractions. α and β proportionality coefficients for linear and quadratic components. 12

13 DIFFERENTIAL TISSUE RESPONSE Different tissues respond differently depending on α and β or their ratio α/β α/β = 10 Gy for Early Responding Tissue (e.g. skin & mucosa) and Many Tumors α/β = 2 to3 Gy for Late Responding Tissues 13

14 TUMOR CONTROL PROBABILITY A unicellular hypothesis: A single surviving cancer cell is sufficient to regrow the tumor if further invoked. Probability that no cancer cells survive 14

15 TUMOR WITH A NUMBER OF SUBUNITS 15

16 TUMORS ARE SUPER PARALLEL 16

17 REGENERATES FROM ONE SUBUNIT 17

18 TCP FORMULA Poisson distribution: S is the overall surviving fraction after a course of radiation therapy N is the initial number of cancer cells 18

19 NORMAL TISSUE COMPLICATION PROBABILITY (NTCP) We want this to be as low as possible! Many models exist If you love math and biological response models read TG-166 and learn more 19

20 Tumor Control Probability (TCP) curves The relationship between total dose and response (e.g. tumor control or normal tissue injury) is threshold-sigmoid. Above a certain threshold tumor control and complication rates increase steeply 20

21 Factors affecting shape and slope of TCP curves The fundamental goal in radiation oncology is to deliver a sufficiently high dose of radiation to sterilize the tumor cells with minimal damage to the surrounding normal tissues, with the ultimate result being complete eradication of the tumor with sufficient normal tissue remaining to ensure viability and function. Problems: interaction of radiation in matter, including cells, tissues and organs, is a nonspecific, random process, with no specificity to tumor cells; radiation delivered from the sources outside the body is absorbed by normal tissues in its path to the tumor, and the damage to the normal cells occurs. Tumor Control Probability (TCP) curves 21

22 Normal tissue complication probability (NTCP) curves 22

23 Influence of normal tissue regeneration on responses. Normal tissue tolerance. As in the tumor, more cells are killed in the normal tissue as the dose is increased and the probability of damage occurring increases. However, all normal tissues have a limit as to the amount of radiation they can receive and still remain functional; this is defined as Radiation tolerance The amount of radiation used to treat a specific malignant tumor is limited by the tolerance of the surrounding normal tissue, not by the tumor. 23

24 TCP: MODELING PROBLEMS TCP endpoint = local control but at what time? Where is the tumor? Tumor localization on planning images? Multi-modality imaging? Local failure or marginal miss? What was the delivered dose distribution? Role of setup errors, organ motion? Uncertainty in radiobiological parameters. 24

25 PROBLEMS WITH MODELING NTCP Reported clinical data mostly for low NTCP and low (<70 Gy) doses. If NTCP increases sigmoidally with dose, most data are on the early tail extrapolation is troublesome Several types of complications per organ Different onset times, dose-volume dependencies Non-radiation factors affect NTCP Most models quantize the complication Most complications show severity continuum 25

26 NORMAL TISSUE COMPLICATIONS SPINAL CORD Complications = Radiation myelitis Clinically-want NTCP << 5% 1991 (E&B) TD5 ~ Gy, TD50 ~ 70 Gy Updates TD5~57 Gy Weak volume dependence confirmed Small α/β (~2 Gy) Some occult injury recovery (~2 yrs) 26

27 NORMAL TISSUE COMPLICATIONS LUNG Complication=severe radiation pneumonitis Requiring serious medical care NTCP~20-25% (steroids) accepted Onset within 6 months of Tx TD50(1) ~28 Gy Good DVH correlates for treatment planning: D mean Volumes receiving >13 Gy, >20 Gy, >30 Gy Are some sub-volumes more sensitive than others?? 27

28 Bad news NTCP Models are much too simplistic to describe physiology of radiation damage. Maybe we shouldn t try! Good news-maybe we don t need very sophisticated models Crudely, there are 3 types of normal tissues: Max dose [serial?] tissues (cord, optic structures, bowel) Mean dose [parallel??] tissues (lung, liver, parotids) Mixed tissues (rectum) look at middle parts of DVH Such surrogates for NTCP are easily obtained from DVH They are used in clinical decisions and IMRT optimization (mean lung dose < 21 Gy, Max cord dose < 50 Gy) More good news: Lots of data from modern clinical studies! NTCP: SUMMARY 28

29 THERAPEUTIC RATIO The ideal situation is when the dose-response curve for damage in the critical normal tissue sits well to the right to higher total doses) than that for tumor control. In this case, the dose that gives a 90% probability of tumor cure may give less than 10% probability of normal tissue damage. Unfortunately, in most cases the two doseresponse curves lie close to each other. 29

30 GENERALIZED EQUIVALENT UNIFORM DOSE (GEUD) Defined as the uniform dose that, if delivered over the same number of fractions as the non-uniform dose distribution of interest, yields the same radiobiological effect. 30

31 GEUD FORMULA Fractional organ volume receiving dose Tissue specific parameter 31

32 GEUD FORMULA METAPHORICAL EXAMPLE General Effective Food Dose You eat a snack that consists of protein, carbohydrates, and fat. Want to know its caloric equivalent if your snack were just carbohydrates, or just protein, or just fat. 32

33 GEUD FORMULA METAPHORICAL EXAMPLE Understanding: Fractional organ volume receiving dose is the fraction of your snack that is carbohydrate, fat, or protein. would be the calories per gram for the respective nutrient (carbohydrate, fat, protein). 33

34 GEUD FORMULA METAPHORICAL EXAMPLE This snack will have a different Effective Food Dose depending on who is eating it. A professional athlete s body will need a different amount of calories than say... 34

35 GEUD FORMULA METAPHORICAL EXAMPLE 35

36 GEUD FORMULA METAPHORICAL EXAMPLE Understanding: Tissue specific parameter would represent their body s specific response to the snack 36

37 GEUD FORMULA METAPHORICAL EXAMPLE Understanding: The sum of the components to the 1/a is your Effective Food Dose 37

38 COMING BACK TO REALITY Now think of as a fraction of an organ Think of as a radiation dose rather than an amount of calories Associate with the radio-sensitivity of an organ 38

39 WHAT ARE TYPICAL TREATMENT GOALS? Goal I: achieve a sufficient target dose Goal II: do not exceed acceptable doses in normal organs Goal III: target dose should be conformal, spare generic normal tissue Goal IV: do not exceed target maximum dose (with some leeway) Goal III and IV follow from the paradigm of conformal radiotherapy, for which there are no biological models! Therefore: mix of biological and descriptive cost functions necessary 39

40 REAL WORLD RADIOBIOLOGICAL IMPLEMENTATION CMS Monaco Philips Pinnacle Varian Eclipse RaySearch RayStation 40

41 CMS MONACO Implements three biologically based cost functions Poisson statistics cell kill model Serial complication model Parallel complication model 41

42 CMS MONACO 42

43 PHILIPS PINNACLE Pinnacle 3 (V8.0h) incorporates biological optimization features into its P 3 IMRT inverse treatment planning module. Biological objective functions were developed by RaySearch Laboratories. Three biological cost functions Min EUD Target EUD Max EUD 43

44 EQUIVALENT UNIFORM DOSE The concept of EUD was designed to describe dose distributions with a higher clinical relevance Enter a prescription which applies to the structure as a volume rather than fixating on specific dose points Raise or lower equivalent dose to the entire structure as a whole 44

45 EQUIVALENT UNIFORM DOSE Target volumes EUD is the desired dose parameter Prescribed dose 45

46 EQUIVALENT UNIFORM DOSE Normal structures EUD is the maximum tolerable uniform dose May be D 5 or D 50 The uniform doses that lead to 5% or 50% complication probability respectively Typically falls somewhere between the minimum and mean dose 46

47 EQUIVALENT UNIFORM DOSE EUD based optimization can improve the sparing of critical structures while maintaining the same or better target coverage 47

48 EQUIVALENT UNIFORM DOSE EUD simplicity Same formalism is applied to both tumors and normal structures Less input required by user EUD mimics the biological response to dose more closely than do dose volume relationships Higher degeneracy of EUD enables EUD-based optimization to explore a large solution space compared with dose-volumebased objective functions Can find solutions that may otherwise not be apparent 48

49 EQUIVALENT UNIFORM DOSE In short, EUD prescription based planning is a viable and good option High doses may be given to the target while simultaneously maintaining low doses to normal structures in a way that may not be achievable with physical dose constraints 49

50 PHILIPS PINNACLE 50

51 PHILIPS PINNACLE Two plan evaluation tools: NTCP/TCP Editor Used to obtain NTCP and TCP estimates. Biological Response panel Calculation of NTCP and TCP Compare alternate treatment plans side-by-side Graphical representation of NTCP/TCP for each structure Composite estimates of NTCP, TCP, and probability of complication-free tumor control for the entire plan 51

52 PHILIPS PINNACLE 52

53 VARIAN ECLIPSE Eclipse (V10.0) and on provide biological optimization through the use of a plug-in to a RaySearch Laboratories application. All patient and plan information is sent to the the application for fluence optimization by a separate rapid calculation algorithm. Fluences then sent back to Eclipse dose engine for final calculation. 53

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55 VARIAN ECLIPSE Biological plan evaluation: NTCP and TCP values for structures Evaluate NTCP and TCP value change due to: Fractionation schedules (e.g. twice vs. once per day) Changing number of fractions Scaling total dose Two additional graphs LQ-Scaled DVH (showing effective DVHs) Radiobiological Response graph (plotting NTCP and TCP values versus a scale factor for the total dose) 55

56 RAYSEARCH LABORATORIES RAYSTATION RayBiology: radiobiological evaluation, comparison, correction, and optimization of treatment plans. Not discussed in TG-166 Utilizes: geud TCP NTCP More RaySearch Laboratories designed radiobiological optimization and evaluation for Pinnacle and Eclipse. 56

57 THE NEXT FRONTIER 57

58 THE NEXT FRONTIER User should have multiple biological models for evaluation Integrate new evolving technologies as they emerge We want the capacity to compare models Allow the capacity to use a hybrid approach Combine physical dose constraint techniques with biologically based techniques Weight accordingly 58

59 THE NEXT FRONTIER User optimization User can REWARD Getting lower NTCP than Requested Maximizing the TCP for a given NTCP Define stop values for iteration during optimization User will define values below which further optimization is unnecessary improve optimization 59

60 THE NEXT FRONTIER User can input dose modifying factors Help Assess the variations in Outcome Dose Modifying Factors to Include: Chemotherapy Pre-Existing Conditions Dose Sensitivities of Organs Dose Resistance of Organs 60

61 Interaction of radiotherapy and chemotherapy - Decreased tumor cell repopulation following fractionated radiation due to effects of chemotherapy - Increased tumor cell recruitment from G0 into a therapyresponsive cell cycle phase - Increased tumor cell oxygenation following radiation with improved drug or radiation activity - Improved drug delivery with shrinkage of tumor - Early eradication of tumor cells preventing emergence of drug and/or radiation resistance - Eradication of cells resistant to one treatment modality by the other treatment - Cell cycle synchronization - Inhibition of repair of sublethal radiation damage or inhibition of recovery from potentially lethal radiation damage Adjuvant or combined treatments on therapeutic ratio 61

62 THE NEXT FRONTIER Accessible and Interactive with other Medical Information Systems Algorithms available to evaluate effect of other predictive models Patient Specific Probability Metric Ability to recognize non achievable plan requests Desire: Maximize TCP: Minimize NTCP 62

63 THE NEXT FRONTIER Models should address radiobiological variations of tumors Goal: Possibly to generate highly non-uniform dose distribution based on PET and MRI Variations Clonogenic cell density Radiosensitivity Hypoxia Link the Biology to functional images Painting by Number approach 63

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65 RESULTS FDG uptake positively correlated with hypoxia FDG uptake negatively correlated with blood flow FDG uptake negatively correlated with cellular proliferation 65

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67 CORRELATION CONFIRMED IN HUMAN CANCER CELLS Oxygenation of human cancer cells was controlled Decreasing the oxygenation of the cells increased its affinity to absorb FDG Patients had squamous cell carcinoma of the head and neck Cell lines (UT-SCC-5) and (UT-SCC-20) 67

68 WHY CARE ABOUT OXYGENATION? 68

69 HYPOXIC VS OXIC 69

70 HYPOXIC VS OXIC Increased resistance to radiation with decreased oxygenation (hypoxic) Non-uniform PET image means non-uniform levels of oxygenation Non-uniform oxygenation means nonuniform radio-sensitivity Why have uniform dose? 70

71 TG-166 RECOMMENDATION???????? TG-166 maintains that highly non-uniform dose distributions caused by the optimization technique (as opposed to deliberate and tested nonuniformity as seen in SRS, SIB techniques, and brachytherapy) should be avoided. This should be challenged on the merits of: SRS SIB Brachytherapy 71

72 BRACHYTHERAPY ISODOSE 72

73 BRACHYTHERAPY VS IMRT DVH 73

74 CYBERKNIFE ISODOSE (54 GY 3FX) 74

75 CYBERKNIFE DVH (54GY 3 FX) 75

76 GAMMAKNIFE ISODOSE 76

77 GAMMAKNIFE DVH 77

78 HETEROGENEOUS DOSE: SUPPORT Adds another degree of freedom to treatment planning More opportunity to modulate and spare critical structures Hot spots may located in GTV and not detrimental Tumors are Heterogeneous. Why should Dose be Heterogeneous? 78

79 INTEGRATING HETEROGENEOUS DOSE Using FDG PET scans to define where to escalate dose Integrated boost of areas with highest PET uptake 79

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81 PET DEFINED INTEGRATED BOOST Blue PTV treated to 66 Gy Magenta PTV treated to 82 Gy 81

82 THE NEXT FRONTIER Ability to consider: Time effects Fractionation schema Treatment breaks Tumor growth Delivery time Recurrences Parameter sensitivity analysis How does one parameter affect another parameter 82

83 CONCLUSION Radiobiology is truly an uncharted frontier We have learned a lot, but have a lot more to discover A lot of great radiobiologically based models and tools exist We need to start using them We need to continue making what we have even better It is truly a great time to be in the field! 83

84 RESOURCES Zellmer, D. Comparison of Treatment Planning Systems for IMRT Using Biological Modeling [PDF document]. Retrieved from Ahmed, M. Lecture 19 [ppt]. Retrieved from The Use and QA of Biologically Related Models for Treatment Planning. Rep. no. TG-166. College Park, MD: American Association of Physicists in Medicine, Print. Hall, Eric J., and Amato J. Giaccia. Radiobiology for the Radiologist. 7th ed. Philadelphia: Wolters Kluwer Health/Lippincott Williams & Wilkins, Print. 84