Dosimetric Uncertainties and Normal Tissue Tolerance Ellen D Yorke Memorial Sloan Kettering Cancer Center New York City
Traditional accuracy/precision goal is to deliver external beam radiation therapy to within 5% of the dose prescribed at least with regard to factors under physics control ICRU Report 24 (2 SD), AAPM Report 13 of TG24 (2 SD), TG40, TG142 less explicit Why? There has long been evidence that larger uncertainties can lead to adverse clinical consequences
Evidence from deliberate trials and serious events Some early studies noted dose responses 10% dose change, 10% complication change
2 incidents cited by Dutreix (Radiother/Oncol 1984) 11/70 3/71, Institut Gustave Roussy: Skin and bowel normal tissue reactions noted in patients treated to whole pelvis (50 Gy/5 weeks). Traced to ~10% overdose due to linac miscalibration; 88 patients were treated in this group 1967, Institut Gustave Roussy: Trial tonsil cancer patients were treated with either photons or electrons (2.5 Gy x 18 fx in 40 days). Electrons were observed to be significantly less efficient and trial was discontinued. Electrons were found to be incorrectly calibrated (7%) Clinical trials on skin reactions in electron treatments: L and R sides of each patient served as the two arms. Reactions discriminated 10% dose differences Wambersie et al, 1974; Turesson and Notter, 1976
Normal Tissue Complication Probability (NTCP) NTCP=50%, Dose=D50 High complication incidence unacceptable except for minor effects; region explored by catastrophic errors Bad complications aim to keep <<1% Moderate complications accept if payoff is cure D50=Dose for 50% probability of complication γ50= NTCP (%)/ %, evaluated at D50 Similar definitions of normalized slopes γ C% at C% complication Many different functions used to represent sigmoidal response Different complications, fractionations, clinical scenarios have different dose locations, slopes (D50, γ50 ) Tolerance dose : Dose below which NTCP is clinically acceptable
Quick and dirty estimates For systematic dose error of p%, estimate change in probability of a complication of interest as ~ p * γ50 Normal tissue γ50 s from the literature are rather low In recent consensus (QUANTEC*) reviews, γ50 s range from ~0.9 to 4, depending on the complication 5 % systematic dose increase (e.g. a calibration error) could raise NTCP from expected to 4.5% to 20% higher A clinician may suspect a problem after 10 50 patients for the higher γ50 s Design test frequency to prevent such errors from becoming systematic (TG40, TG100, Thomadsen) Modern knowledge of NTCP is consistent with earlier accuracy/precision physics goals * IJROBP 76, 2010, http://www.aapm.org/pubs/quantec.asp
Population variation: One reason consensus γ50 s are small A more tightly defined population may show sharper response QUANTEC, Jackson et al IJROBP 76 γ50 ~1 Distribution of binary responses NTCP Early work goes back to 80 s Goitein (1987), Thames et al (1989), others..
0.8 0.7 0.6 T spine Probability 0.5 0.4 0.3 0.2 0.1 0 40 50 60 70 80 Equivalent dose in 2-Gy fractions Shultheiss et al, QUANTEC, IJROBP 76 For Grade 2 myelopathy, in the clinically acceptable region of very low complication (D<50 Gy), slopes are much lower and a 10% dose error might only raise NTCP to ~1% Myelitis is a late complication with a latency 1 yr Patients at risk often have poor survival These complications may be hard to detect clinically
Modern Radiation Therapy Calibration related dosimetric uncertainties tight (< ±2%, photons*) Institutional safety culture reduced errors RPC, ~1800 clinical sites Other dose based uncertainties include Dosimetric measurement uncertainties (Sc, Sp, TMR, etc) TPS calculation and commissioning uncertainties Systematic for single machine, department, TPS; may be random over population *Appendix D.5, Handbook of Radiotherapy Physics, Mayles, Nahum, Rosenwald
Uncertainties introduced by dose calculation algorithms and TPS peculiarities can cause problems when combining multi institutional data or adopting new dose and dose volume normal tissue constraints. Physics based uncertainties broaden the effective response curve derived from combined data*. Physics errors can skew the results *Petterson et al, Radiother and Oncol 2008
MUs were calculated without inhomogeneity correction Green DVHs without, Yellow DVHs with inhomogeneity correction Monte Carlo ( true ) mean lung dose 8% larger than TPC prediction Inhomog corrected ( true ) cord s D Max ~ 1.7% lower, high dose region lower than TPC prediction MC cord D Max 0.5% larger (and < high dose volume)
A clinic can base internally consistent, safe, effective guidelines on experience but change requires care Suppose a particular complication rate is acceptable if TPS calculated metric M (e.g. mean dose) M* TP. Suppose their dose calculation algorithm is imperfect such that delivered normal tissue metric, M* del > M* TP (lung on last slide) Suppose they get a new, accurate TPS but continue to use their old planning constraint. Now M* del = M* TPnew and. Treated dose now lower than before Safe, but may be stinting on target coverage If inequalities between M* TP and M* del are reversed (e.g. PA cord on last slide) and there is large enough difference, complication risk might increase Similar considerations hold if a clinic adopts normal tissue constraints from a publication or protocol without checking on calculation, organ definition, and delivery conditions. Mijnheer, 1987
Modern Radiation Therapy Treatment techniques are more demanding than those of the 2D era, making sources of uncertainty other than dose calibration and basic machine parameters more important
Single PA field 1 field Insensitive to setup errors Conventional fractionation Paraspinal SBRT 8 IMRT fields Sensitive to setup error SBRT/Hypofractionated Yellow= plan (no setup error) Green = 3 mm random setup error Cyan= 3 mm AP systematic Dmax=100% Dmax=111% Dmax=121%
Complex dose distributions also raise the question of interpretation of within 5% of the dose prescribed. For NTCP, entire dose distribution in the tissue may be important For many complications/treatment regimens, there is great uncertainty as to the most significant dose/volume combinations APPA IMRT
Different complications depend differently on dose distribution Volume effect (Emami et al, IJROBP 1991) Partial organ irradiation Zero dose Volume fraction=1 v Uniform Dose D Volume fraction=v TD5 (5% NTCP) vs irradiated volume fraction 70 TD5/5 (Gy) 60 50 40 30 Severe RILD Radiation Pneumonitis Radiation Pericarditis Iso complication dose increases as irradiated volume fraction decreases 20 esophageal stricture 10 0 0 20 40 60 80 100 120 radiation myelitis (reference length 20 cm) Weak vs strong volume effects % Organ Irradiated
Volume Dependences and Geometric Uncertainties Weak volume dependence: serial type complication (myelitis) XXXXXXXXXXXXX as bad as XXXXXXXXXXXXX Clinically limit and evaluate high dose end of dosedistribution (Dmax, D05, D1cc) Sensitive to geometric uncertainties for steep dose gradients Could be risky if planners push constraints to the limit Similar sensitivity for small organs (cochlea, optic nerves) regardless of their intrinsic volume effect
Volume Dependences and Geometric Uncertainties Strong volume dependence, parallel type complications (pneumonitis, xerostomia) OK Complication XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX vs XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX Clinically limit and evaluate mean dose, assorted V Dose points and modeled NTCP Relatively insensitive to geometric uncertainties if organ is large relative to both the geometric uncertainty and the dose gradients in the organ.
Volume Dependences and Geometric Uncertainties Intermediate volume dependences (rectal complications) Clinically evaluate with V Dose points and models Regardless of volume dependence, uncertainties due to organ motion and changes affect the delivered dose and (?) complication incidence Physics efforts underway to control these Respiratory motion Breath hold, compression, respiratory gating, tracking Treatment related tissue changes Mid course imaging, adaptive planning Random internal motion (e.g. bowel filling and gas) Pre tx imaging, image based tracking or gating
Fractionation and time Basic Linear Quadratic (LQ) model Additional terms for repair, repopulation D= Dose (Gy) in N short, well separated fractions ; d=d/n Complication dependent biological parameter α/β α/β ~ 1 5 Gy for late complications, higher for acute Biologically Effective Dose (BED)=D (1+d/{α/β} ) For familiar magnitudes, use Equivalent Dose in 2 Gy fractions (EQD2 or NTD2); EQD2=BED/(1+2/{α/β} ) Systematic dose uncertainties affect BED through D and d Size of effect depends on α, d
Models attempt to summarize all these effects Popular models: Lyman model, generalized equivalent uniform dose (geud), relative seriality model geud is a non judgmental version of the Lyman model geud = Lyman Effective Dose Models combine the full DVH (or BEDVH) and other data to arrive at a single plan specific metric Other data: spatial distribution, medical variables, time Metric may be NTCP or a non judgmental surrogate ( geud) For many reasons (biological, clinical, cultural *and overall difficulty) models and dose/volume metrics have large uncertainties. Fortunately, we usually know enough to stay safe for error free treatments delivered with small physics related uncertainty. See The Lessons of QUANTEC, IJROBP 76, #3 Suppl
The normal tissue dose response is often expressed in measures of the organ dose distribution other than dose: geud (mean dose a special case), D Vol, BED Vol, EQD2, geud with LQ corrections, etc.
QUANTEC
Random errors In modern RT, most random errors come from daily setup variations (SD s typically < 3 mm) and organ motion; for multi fraction treatments, these blur the dose distribution; often handled by convolving the planned beam dose distribution with an appropriate Gaussian. Random errors usually have little impact on normal tissue complications Exceptions: treatments with sharp dose gradients surrounding serial responding normal structures
Systematic errors In addition to systematic dose output and computational uncertainties, normal tissue dose distributions are affected by systematic setup errors and systematic organ motion or physiological deformation effects Studies of systematic setup error effects often use Monte Carlo type simulations which shift isocenter for each base plan N times according to an evidence based setup error distribution (usually with mean=0, SD= ) Results are organ and treatment technique specific. H&N: Siebers et al, IJROBP 63; Lung: Schwarz et al, IJROBP 65; Rectum: Fenwick & Nahum and Fenwick Med Phys 28,
Simulation study of setup errors 24 patient IMRT plans Random setup error handled by fluence convolution Systematic setup error simulated by random shifts of isocenter + dose recalculation, 50 shifts/pt Cord D 2 (serial type complication) more variable than Parotid mean dose (parallel type complication)
From Siebers et al, simulations based on H&N IMRT plans of 24 patients
Clinical methods to control deformation systematic effects Treatment protocols (e.g. sim and treat with empty stomach or rectum) Adaptive replanning (e.g. mid course planning scans to assess normal organ changes due to tumor changes)
Hypofractionation (HFX) NTCP for hfx is even less well understood than for conventional fractionation. Unusual complications (fortunately rare) are clinically observed LQ model applicability is questioned Assuming LQ: dose response is compressed (steepened) in absolute dose but γ50 (relative dose) is not greatly changed. Bad news: Sharp gradients make HFX more susceptible to setup errors. Good news: Meticulous QA is standard of care (TG101 http://www.aapm.org/pubs/reports/rpt_101.pdf) Most uncertainties are systematic for single or few fraction treatments
Dmax=100%, ideal Dmax=111%, 3mm random Dmax=121%, 3mm syst Medin et al, IJROBP 2011 Fig. 3. Dose response curve for motor neurologic deficit with 95% confidence interval
Physical uncertainties in clinical trials Petterson et al, Radiother and Oncol 2008 Physics uncertainties broaden the response curve so trials would have to be larger to discriminate an effect if there are large physics uncertainties But with 5% SD, physics uncertainties γ50 ~ 8. NTCP response curves are already much broader ( γ50 <5). There is little benefit in terms of trial arm numbers to improving routine physics precision until reasons behind shallow NTCP responses are better understood.