Radiation Biology Notes PDF - Effects and Cell Survival - Study Guide

Okay, here's the conversion of the provided text into a structured Markdown format. ### B.1.3 Radiation Biology **I. Radiation effects** i) Basic concept of Radiotherapy: trade-off between tumor control and effects. Here is the description of the diagram in the image: The graph illustrates the...

Okay, here's the conversion of the provided text into a structured Markdown format. ### B.1.3 Radiation Biology **I. Radiation effects** i) Basic concept of Radiotherapy: trade-off between tumor control and effects. Here is the description of the diagram in the image: The graph illustrates the trade-off between tumor control probability (TCP) and normal tissue complication probability (NTCP) as a function of radiation dose. The x-axis represents the dose, while the y-axis represents the effect (probability). * TCP: Tumor control probabilility * NTCP: Normal Tissue complication probability ii) The cell as a target: * 70%-80% water, 20-30% proteins, lipids. * Cell nucleus: DNA, primary target. * Direct and indirect (via radicals) effects. **DNA damage** * Single-strand breaks (repairable, sublethal) * Double-strand breaks (lethal) * Clustered damage * Repair iii) Cell death. * Reactions after radiation damage * Complete repair * Survives with mutation/damage → tumor * Death after a few cell cycle's * Cell death within hours (apoptosis) **II. Cell Survival Curves** Number of surviving cells as a function of dose. i) Clonogenic assay * Cells * Single cell in medium in vitro * Incubator **Procedure** * Detach cell (enzyme trypsin) * Plating of N cells * Irradiate with dose D * Incubate for 1-2 weeks * Stain & count colonies $N_{col} (D)$ **Evaluation** * Control group with D = 0 * Plating efficiency $p = \frac{N_{col}(0)}{N} < 1$ * Irradiated samples * Surviving fraction $S(D) = \frac{N_{col}(D)}{p \cdot N}$ Here is the description of the diagram displayed in the image The graph shows the "log S(D)" along the y-axis and "D[Gy]" along the x-axis. * $N_{col}$ too small ⇒ bad statistics * $N_{col}$ too large ⇒ colonies overlap * Vary $N_{col}$ depending on D. ii) The target-hit model **Assumptions:** * Ionization events are statistically distributed * $n$ targets in cell, which need to be hit for inactivation **Single-target - single-hit** * 1 target per cell; cell dies for ≥1 hits * D = Dose, cell density, target size * $µ$ = mean number of hits per cell * $µ = \frac{1}{D_0} \cdot D; D_0$ dose for which µ = 1 * Number of hits k. Poisson distributed $P(k) = \frac{µ^k}{k!} e^{-µ}$ $S(D) = P(k=0) = e^{-µ} = e^{-\frac{D}{D_0}}$ **Multi target-single hit** * n targets per cell, all of which need to be hit at least once for cell death. | Probabilities for... | | | :---------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------- | | target i not hit | $e^{-\frac{D}{D_0}}$ | | target i hit at least once | $[1 - e^{-\frac{D}{D_0}}]$ | | all u targets hit at least once | $[1 - e^{-\frac{D}{D_0}}]^n$ | | cell survives | $1 - [1 - e^{-\frac{D}{D_0}}]^n = S(D)$ | | for n=1 | $S(D) = e^{-\frac{D}{D_0}}$ | | for high dose | with $e^{-\frac{D}{D_0}} small, \text{ i.e. } [1-e^{-\frac{D}{D_0}}]^n \approx 1 - ne^{-\frac{D}{D_0}} \Rightarrow S(D) \approx ne^{-\frac{D}{D_0}}$ | | for low dose | with $e^{-\frac{D}{D_0}} small, \text{ i.e. } e^{-\frac{D}{D_0}} \approx 1 - \frac{D}{D_0}$ | | | $\Rightarrow S(D) \approx 1-[1-(1-\frac{D}{D_0})]^n$ | | | $1-[\frac{D}{D_0}]^n \approx 1$ | iii) The linear quadratic model * 2 parameters: $\alpha, \beta$ * $S(D) = e^{-\alpha D + \beta D^2}$ * $[\alpha] = \frac{1}{Gy}$ , $[\beta] = \frac{1}{Gy^2}$ * $e^{-\alpha D} $ $S(D) = e \\ for D \approx 0: S(D) \approx e^{-\alpha D} \\ for high D: \beta - term dominates$ * Influence of both terms equal at dose $D'$ $\alpha D' = \beta D'^2 \implies D' = \frac{\alpha}{\beta} [Gy]$ * Strength: good fit to exp. data for $D = [1 ... 10 Gy]$ * For higher doses: $\beta D^2$ too strong ⇒ target-hit better Mechanistic Interpretation (careful) Two ways of cell inactivation a) 1-track-event eg, DSB by 1 particle proportional to D $\implies∝D$ b) 2-track-events eg, two SSB by 2 particles, close together proportional to $D^2 \implies \beta D^2$ Cell with high repair capacity: strong shoulder i.e, small α/β ratio *Here is the description of the curve displayed in the image* The graph shows the "Tumors: high α/&beta" along the y-axis and "D" along the x-axis. Fractionation in LQM * N irradiations with $d = \frac{D}{N} $ sufficiently separated (~1d) $S_1 = e^{-\alpha d - \beta d^2} \\ S_2 = S_1 \cdot e^{-\alpha d - \beta d^2} \\ S = e^{-(\alpha d + \beta d^2) \cdot N} = e^{-\alpha D + \beta \frac{D}{N}}$ * Linear Term **is not** changed * For $\beta \approx 0$: no effects of fractionation * for $\beta \implies 0$: no effects of fractionation * large fraction effect for low α/β * low α/β: "late reacting tissue", e.g spinal cord * "spared" by fractionation * high α/β : "early reacting tissue", e.g tumors, skin *fractionation effects are tissue depended * sparing of normal tissue **Typ. values in radiotherapy:** $D = 60 Gy, d=2Gy, N = 30, T = 40 days$