Stochastic Effects and Late Tissue Reactions of Rad in Organ Systems

radiation induced damage at the cellular level may lead to

measurable somatic and hereditary damage in the living organism as a whole later in life

late effects

long term results of radiation exposure

examples of measurable late biologic damage

cataracts, leukemia, genetic mutations

epidemiology

science that deals with the incidence distribution, and control of disease in a population

irradiation related cancer risk is determined by

comparing natural cancer rates in general populations and use the comparisons to establish risk factors for the general population

the most significant late stochastic effect caused by exposure to ionizing radiation

cancer

this effect is a random occurrence that dose not seem to have a threshold and for which the severity of the disease is not dose related

late stochastic effect - carcinogenesis

demonstrated graphically through a curve that maps the observed effects of radiation exposure in relation to the dose of radiation received

radiation dose response relationship

the observed effects of radiation exposure may be

the incidence of a disease or the severity of an effect

the DR curve can be

linear or non linear

sigmoid (s-shaped) threshold curve of radiation dose response relationship is generally employed in

radiation therapy to demonstrate high dose cellular response

threshold

point at which response or reaction to an increasing stimulation first occurs

with reference to ionizing radiation, threshold means that

below a certain radiation level or dose, no effect is observed

biologic effects begin to occur only when

the threshold level or dose is reached

nonthreshold indicates

a radiation absorbed dose of any magnitude has the capability of producing a biologic effect

for linear nonthreshold curve biologic effect responses will be cause by ion rad in living organisms in a

directly proportional manner all the way down to dose levels approaching zero

because of nonthreshold relationship no radiation dose can be

considered absolutely safe with the probability of biologic effects increasing directly w/ magnitude of absorbed dose

stochastic and hereditary effects at low dose levels from low-LET rad (like E for diagnostic rad) appear to follow a

linear-quadratic nonthreshold curve

Currently the committee recommends the use of what curve for most cancers

linear non-threshold curve of radiation dose

LNT curve implies that the

biologic response to ionizing radiation is directly proportional to the dose received

BEIR Committee believes the linear-quadratic nonthreshold curve (LQNT) is more accurate reflection of

stochastic somatic and genetic effects as low-dose levels from low-LET radiation

leukemia, breast cancer, and heritable damage are presumed to follow

LQNT curve

acute reactions from significant radiation exposure may be demonstrated graphically through the use of a

linear threshold dose response curve

biologic response does not occur

below a specific dose level

what provided the foundation for the linear threshold dose response curve

lab experiments on animals and date from human populations observed after acute high doses of radiation

sigmoid or S-shaped (nonlinear) threshold curve of radiation dose response relationship is generally employed in

radiation therapy to demonstrate high-dose cellular response to the radiation absorbed within specific locations such as skin, lens of eye, various blood cells

s shaped threshold curves are caused by

some healing occuring and then cell death

continued use of the linear dose response model for radiation protection standards has potential to

exaggerate seriousness of radiation effects at lower dose levels from low-LET

continued use of the linear dose response model for radiation protection standards accurately reflects

effects of high-LET at higher doses

regulatory agencies tend to be

conservative (overestimate risk)

when living organisms exposed to radiation sustain biologic damage it is called

somatic effects

types of somatic effects

stochastic effects or tissue reactions

stochastic effects

probability that effect happens depends on received dose but severity does not (i.e. cancer) AKA probablitic

tissue reactions

both the probability and the severity of the effect depend upon the dose (i.e cataracts) AKA deterministic

late somatic effects

consequences of radiation exposure that appear months or years after such exposure

late somatic effects may result from

previous whole/partial body acute exposure, previous high radiation doses, long term low level doses sustained over several years

late effects can be

either stochastic or tissue reactions

late tissue reactions

cataract formation, fibrosis, organ atrophy, loss of parenchymal cells, reduced fertility, sterility

teratogenic effects

embryonic/fetal/neonatal death, congenital malformations, decreased birth weight, disturbance in growth/development, increased still birth, infant mortality, childhood malignancy, childhood mortality

stochastic effects

cancer, genetic (hereditary) effects

three adverse health consequences that require study at low level of exposure

cancer induction, damage to the unborn from irradiation in utero, genetic (hereditary) effects

theoretically, radiation damage to just one or a few cells of an individual could produce a

stochastic effect like malignancy or hereditary disorder many years after radiation exposure

extreme reactions associated with high skin doses may

persist for some time, but occur within weeks/months after exposure

three major types of late effects are

carcinogenesis, cataractogenesis, embryologic effects

stochastic effects

carcinogenesis and embryologic effects

at low equivalent doses below 0.1 Sv

the risk of cancer is not directly measurable in population studies

why are lose doses below 0.1 Sv risk is not measurable because

risk is overshadowed by other causes of cancer in humans, risk is zero

current radiation protection philosophy

utilizes the linear non-threshold dose response relationship and assumes that risk still exists, may be determined using high dose data to low dose data (controversial)

absolute risk model

predicts a specific number of excess cancers will occur per unit of radiation dose, per population size, per time period, regardless of the natural incidence of cancer

absolute risk model assumes

radiation adds a fixed, additional risk to the background (spontaneous) cancer rate

example of the absolute risk model

if 5 cases of cancer occur naturally in a population of 1,000 per year, and radiation exposure is predicated to cause 2 extra cases, the total becomes 7 cases per year (5 natural + 2 radiation induced)

relative risk model

predicts that radiation exposure will multiply the natural (baseline) incidence of a cancer by a certain factor

relative risk model assumption

the risk is proportional to the baseline cancer rate

example of relatige