10: Radiation dose in computed tomography

Exposure

The radiation quantity, exposure, refers to the concentration of radiation at a particular point on the patient. Exposure is easy to measure with an ionization chamber positioned at the point of measurement. Radiation falling on the chamber ionizes the air in the chamber to produce ion pairs (charges). Exposure is a measure of the amount of ionization produced in a specific mass of air by x rays or gamma radiation. The ionization indicates the amount of radiation to which a patient is exposed.

The unit of exposure is the Roentgen (R), the conventional unit, or the coulomb per kilogram (C/kg), the SI unit. One Roentgen produces 2.58 × 10⁻⁴ C/kg of air at standard temperature and pressure. Exposure is reported in the literature in milliroentgens (mR), a much smaller unit (1 R = 1000 mR) or in microcoulombs/kilogram (μC/kg) where 1 R = 258 μC/kg.

Absorbed dose

The absorbed dose, or radiation dose as it is popularly referred to, is the amount of energy absorbed per unit mass of material (patient). Any risk associated with radiation is related to the amount of energy absorbed, and this quantity is particularly important in radiation protection.

The old unit of absorbed dose is the rad (r), which is equal to an energy absorption of 100 erg/g of absorber. The SI unit of absorbed dose is the Gray (Gy), so named in honor of Louis Harold Gray, a British radiobiologist who devised ways to measure the absorbed dose. One Gray is equal to 1 joule per kilogram (J/kg) or 1 r is equal to 0.01 Gy or 100 r is equal to 1 Gy. Relevant submultiples of the Gray are 1 centigray (cGy), which equals 1 r and 1 milligray (mGy), which equals 100 millirads (mrads). For the sake of simplicity, 1 r is approximately equal to 0.01 Gy.

Effective dose

The quantity effective dose, E, previously referred to as the effective dose equivalent, is used to quantify the risk from partial-body exposure to that from an equivalent whole-body dose. The term is used to take into account the type of radiation (because different types of radiation can produce varying degrees of biological damage) and the radiosensitivity of different tissues (because some tissues are more sensitive than others).

As described by McNitt-Gray (2002), E is a “weighted average of organ doses” and can be expressed mathematically as follows:

E = ∑T(DT,R  ⋅  WT  ⋅  WR)

where D_T,R is the absorbed dose to the tissue (T), W_T is the tissue-weighting factor, W_R is the radiation-weighting factor, and the symbol ∑ is the “sum of.” These factors can be obtained from previously calculated tables (Bushong, 2017).

Although the old unit of effective dose is the rem, the SI unit is the Sievert (Sv), where 1 Sv = 100 rem. The effective dose relates exposure to risk. As noted by Brenner (2006), “relevant organ doses for CT examinations are on the order of 15 mSv or less.” Brenner also notes that “there is good epidemiologic evidence of increased cancer risk for children exposed to acute doses of 10 mSv (or more) and for adults exposed to acute doses of 50 mSv (or more).”

To put this into perspective, emphasized that “the total amount of radiation that a patient receives in any radiographic examination is best quantified by the effective dose, which is related to the risk of carcinogenesis, and with the induction of genetic effects. Effective doses with radiographic imaging are smaller than natural background (3 mSv per year). Effective doses from common fluoroscopic and CT examinations are comparable to natural background and may be much higher with interventional radiology procedures.”

It is interesting to recall that the dose limits for occupationally exposed individuals (radiologists and technologists, for example) are given in mSv. The International Commission on Radiological Protection (ICRP) dose limit for radiation workers is 20 mSv per year. Although the dose limits for radiation workers in the United States is 50 mSv per year, it is 20 mSv per year for workers in Canada (Bushong, 2017).

Stochastic effects

Stochastic effects are those effects for which the probability (rather than the severity) of the effect occurring depends on the dose. The probability increases with increasing dose, and there is no threshold dose for these effects. The linear no threshold (LNT) dose–response model is the radiation risk model most favored by radiobiologists in estimating the risk of exposure in radiology (Bushong, 2017). Medical radiation protection standards, guidelines, and recommendations are based on this model.

The LNT dose-response model states that the radiation risk increases as the dose increases and there is no threshold dose. Hendee and O’Connor (2013) stated that the LNT model is more commonly used because it is a simpler and conservative approach, which is more likely to overestimate cancer risk at low doses than to underestimate risk of cancer induction. The authors further stated, however, that because medical imaging doses are so low, there is no evidence that the no-threshold model is effective at estimating cancer induction risk.

Furthermore, even a small dose has the potential to cause a biological effect. There is no risk-free dose. If harm occurs, the damage generally becomes apparent years after exposure; therefore, stochastic effects also are called late effects. Examples of stochastic effects include cancer, leukemia, and hereditary effects. Stochastic effects are considered a risk from exposure to the low levels of radiation used in medical imaging, including CT examinations.

Deterministic effects

Deterministic effects (nonstochastic effects) are those effects for which the severity of the effect (rather than the probability of the effect) increases with increasing dose and for which there is a threshold dose. Below the threshold dose, these effects are not observed. Threshold doses are considered to be relatively high doses that can kill cells and cause degenerative changes in tissues that have been exposed to radiation. Deterministic effects are also referred to as early effects and involve high exposures that are unlikely to occur in medical imaging examinations.

Examples of deterministic effects include skin erythema, epilation, and pericarditis for example. Absorbed doses in CT are substantially lower than threshold doses for the induction of deterministic effects. As patients undergo several examinations, it may be possible to reach the threshold dose for certain deterministic effects.

Types of dosimeters

In the past, several types of dosimeters were used to measure the dose in CT. These include film dosimeters, thermoluminescent dosimeters (TLDs), and specially designed ionization chambers. In 1981, the Bureau of Radiological Health (BRH), now the Center for Devices and Radiological Health (CDRH), introduced what could be noted as a significant step toward CT dose measurement. The method suggested by the CDRH uses a pencil ionization chamber. Solid-state metal oxide semiconductor field effect transistors (MOSFET) are now used in CT dosimetry studies because they are more sensitive than TLDs, they provide an instant readout, and they can be reused immediately. For further details on the methodology for the evaluation of radiation dose in x-ray CT, the interested reader may refer to the American Association of Physicists in Medicine (AAPM) Report No 111 (2010).

Ionization chamber

An ionization chamber is an instrument used to accurately quantify radiation exposure. The ionization chamber shown in Fig. 10.5 consists of a small air-filled container with thin walls that allow radiation to pass through easily. As the high-energy photons (x rays) collide with air molecules enclosed within the ionization chamber, some of the molecules are “ionized” (i.e., one or more electrons are knocked from some molecules). These free electrons can be collected on a conducting wire or plate and measured as electric charge. The amount of collected charge is proportional to the amount of ionization, which is proportional to the amount of radiation that passes through the chamber. The charge is removed from the ionization chamber and measured with a very sensitive instrument known as an electrometer. The total electric charge generated by an x-ray beam is represented by Q and measured in coulombs (1 coulomb = 6.24 × 10¹⁸ electrons).

Phantoms for CT dose measurement

To standardize the measurement of the dose and provide a clinically realistic geometry, the BRH researchers suggested that the ionization chamber be placed in one of two cylindrical phantoms during the radiation measurement. The smaller phantom simulates a patient’s head and the larger phantom simulates a “body” or torso (Fig. 10.6). Both phantoms are 15 cm in length. The diameter of the “head” phantom is 16 cm, and the diameter of the “body” phantom is 32 cm. Both phantoms are solid acrylic with holes drilled through the phantom at specified locations to accommodate the pencil ionization chamber (Fig. 10.7). Acrylic plugs are placed in the holes unoccupied by the ionization chamber. Fig. 10.8 shows a pencil ionization chamber about to be inserted into a CT scanner dosimetry phantom. The holes that are not used for the ionization chamber are filled with acrylic plugs. Careful examination of the plug reveals a small hole that can be seen through its diameter. This hole is centered end to end in the plug and is visible in the CT image of the dosimetry phantom if the x-ray beam is centered on the phantom and passes through the hole. The appearance of the hole in the image verifies that the x-ray beam is striking the center of the phantom.

The procedure for measurement is to place the ionization chamber in one of the phantom holes, take a scan, and record the amount of charge emitted from the chamber. Then the chamber is moved to the next hole, the plug is placed in the original chamber hole, and the procedure is repeated. Moving the chamber to another hole (e.g., from the anterior to the posterior) allows the dose to be determined at a variety of locations within the phantom. Generally, the dose varies among locations, even when the same technique is used. For example, the dose at the anterior location of the phantom differs from the dose at the posterior location, which differs from the dose on the patient’s right side, and so on. It is usually prudent to measure the dose at several locations for a given technique.

Display of CT dose metrics on the scanner

In general, there are four CT dose metrics (to be described subsequently) commonly used in CT, and are typically shown on the dose report that displays on the CT scanner console. These include the CT dose index (CTDI), the dose-length product (DLP), and the size-specific dose estimate (SSDE). The SSDE depends not only on the radiation output from the CT scanner but also the size of the patient. The fourth dose metric of importance in CT, and in any imaging modality using ionizing radiation, is the effective dose.

The International System of Units quantity for the CTDI and the DLP is expressed in milligrays (mGys); it is expressed in millisieverts (mSv) for the effective dose. The effective dose relates the radiation exposure to risk and is considered the best method available to estimate stochastic radiation risk (Wolbarst et al., 2013). Still, effective dose is an estimate only, based on weighting factors applied to the body’s tissue or the organ being irradiated (Hermann et al., 2014).

CT dose metrics and calculation

The earlier dose studies reported CT doses by using various terms to describe the absorbed dose in a CT examination. These included single-scan peak dose, multiple-scan peak dose, dose profile, and others such as multiple-scan average dose (MSAD). These results led the CDRH to introduce and recommend the use of CTDI and MSAD in the Federal Performance Standard as the dose descriptors specific to CT. For example, because the early CT examinations consist of a series of stop-and-go scans (slices), the MSAD was the dose descriptor for use in a clinical situation at that time. The MSAD concept will be highlighted for historical reasons only.

Multiple-scan average dose

The MSAD was the first CT dose descriptor to be identified (Cody & McNitt-Gray, 2006; McNitt-Gray, 2002). To use the MSAD, a series of CT scans is performed on a patient (Fig. 10.9). Between each scan, the patient is moved a bed index (BI) distance. Each slice delivers the characteristic bell-shaped dose represented by the curves at the top of Fig. 10.9. If the doses from all scans are summed, the resulting total patient dose resembles the oscillating curve at the bottom of Fig. 10.9. In the regions where the bell curves overlap, the resultant dose is higher than that from just one scan. If the total dose distribution curve is known (bottom curve), the MSAD (dotted straight line) can be calculated by mathematically sampling the peaks and valleys of the multiple scan dose curve. This can be written as follows:

MSAD = CTDI × SW/Bl(10.1)

where SW is slice width in millimeters and BI is bed index or slice spacing.

Computed tomography dose index

The CTDI was the next CT dose descriptor after the MSAD. It was developed by the US Food and Drug Administration (FDA) and was therefore labeled CTDI_FDA (Boone, 2007). CTDI_FDA has evolved to its present form with several notable changes. These are highlighted in this subsection.

The CTDI_FDA is defined as follows:

CTDlFDA = ln.SW∫−7+7D(z)  dz(10.2)

where n is the number of distinct planes of data collected during one revolution, SW is the nominal slice width in millimeters, D(z) is the dose distribution, and z is the dimension along the patient’s axis. For axial (non-spiral/helical) CT scanners and spiral/helical CT scanners with a single row of detectors, n = 1. For MSCT scanners, n is the number of active detector rows (n = 16) during the scan.

The CTDI_FDA represents the mean absorbed dose in the scanned object volume; therefore, the unit of the CTDI is Gy with relevant submultiples such as cGy and mGy.

This equation is not as complicated as it appears. The integral sign (∫) merely instructs the user to determine the area under a single curve D(z). Fig. 10.10 demonstrates the value of this integral by shading the area under a typical dose distribution curve. If this area is divided by the number of slices times the slice width [(n)(SW)], the result is the CTDI_FDA.

This definition, which was accepted by the International Electrotechnical Commission (IEC, 2001), is good for essentially all shapes of dose distribution curves D(z) that are emitted by CT scanners. Note that increasing the area under the curve can increase the CTDI_FDA. The area can be increased by either increasing the intensity of radiation, which raises the height of the curve, or by widening the curve, usually by opening the x-ray collimators near the x-ray tube. Either case increases the CTDI_FDA and ultimately increases the radiation dose to the patient.

For axial CT scanners, as the slice spacing increases, there is a greater likelihood that relevant tissue will be “missed” (it falls between the slices) in the scan sequence, thus limiting the amount that the BI can be increased. Conversely, when the BI is made smaller, the slices become closer together, more overlap of adjacent dose distributions occurs, and the average dose increases. When the SW equals the BI, the MSAD is numerically equal to the CTDI_FDA.

The CTDI_FDA has evolved from its initial stage of measurement for 14 contiguous slices where the integration would be from –7 to +7. The fixed length of the pencil ionization chamber “meant that only 14 sections of 7-mm thickness could be measured with that chamber alone. To measure CTDI_FDA for thinner sections, sometimes lead sleeves were used to cover the part of the chamber that exceeded 14 section widths” (Cody & McNitt-Gray, 2006; McNitt-Gray, 2002).

This shortcoming was solved by introducing another dose index, the CTDI₁₀₀, which “relaxed the constraint on 14 sections and allowed calculation of the index for 100 mm along the length of the entire pencil ionization chamber, regardless of the nominal slice width being used” (McNitt-Gray, 2002). The index is given by the equation:

CTDl100 = (1/nT)  ∫−5050D(z)  dz(10.3)

where nT is the nominal collimated slice thickness.

The next major change in the CT dose descriptor is the introduction of the weighted CTDI (CTDI_W) to account for the average dose in the x-y axis of the patient instead of the z-axis. This can be done using a phantom where the pencil ionization chamber is positioned in the center (CTDI_center) and at the periphery (CTDI_periphery) of the phantom (see Fig. 10.7). In this case the following algebraic expression can be used to calculate the CTDI_W (as provided by Cody & McNitt-Gray [2006] and McNitt-Gray [2002]):

CTDlw = (1/3) (CTDI100)center + (2/3) (CTDl100)periphery(10.4)

To consider the dose in the z-axis, yet another dose descriptor was developed. This is the CTDI_volume, which can be calculated with the following relationship for spiral/helical CT imaging:

CTDlvolume = CTDlW/Pitch(10.5)

It is important to note that the term pitch has been defined by the IEC as a ratio of the distance the table travels per revolution (in millimeters) to the total nominal beam collimation (in millimeters). For a pitch of 1, the CTDI_volume is equal to the CTDI_W; for a pitch of 1.5, the CTDI_volume is equal to CTDI_W/1.5.

Dose length product

As mentioned earlier, the DLP is yet another dose descriptor used in CT dose studies and reported in the literature and on CT scanners. Although the CTDI_volume provides a measurement of the exposure per slice of tissue, the DLP provides a measurement of the total amount of exposure for a series of scans. The DLP can be calculated if the length of the irradiated volume (scan length) and the CTDI_volume are known by using the following relationship:

DLP = CTDlvolume × Scan length(10.6)

It is important to note that, although the CTDI_volume is not dependent on the scan length, the DLP is directionally proportional to the scan length (Fig. 10.11). DLP is expressed in mGy-cm.

Size-specific dose estimate

Another CT dose metric introduced by the AAPM in 2011 (Tsujiguchi et al., 2018; Waszczuk et al., 2015) to account for patient size is the size-specific dose estimate (SSDE) as the CTDI_volume and DLP do not address smaller pediatric patients. The SSDE takes into consideration the size of the patient to obtain the CTDI_volume. The size dimensions of the anteroposterior (AP) and lateral (LAT) measurements of the patient are used to calculate the effective diameter which “represents the diameter of the circle whose area is the same as that of the patient’s cross-section” (Waszczuk et al., 2015). Furthermore, these dimensions can be “measured using electronic calipers on the axial scans at the center of the scanned volume along the z-axis (cranio-caudal)” (Waszczuk et al., 2015). The effective diameter can be obtained using the following relationship:

Effective diameter = (AP × LAT)(10.7)

The SSDE is obtained using the following equation:

Size-specific dose estimates = ∫size32D × CTDIvol32(10.8)

where fsize32D = a × b−bx is the object correction factor (SSDE conversion factor) and x is equal to the effective diameter of the patient. Coefficients a and b are defined by the AAPM as:

a = 3.704369; and b = 0.03671937. A study by Waszczuk et al., (2015) showed that the SSDE (mGy) mean ± SD for patient sizes of less than 30 cm, between 30 and 35 cm, and greater that 35 cm in routine dose CT were 6 ± 3; 24 ± 5; and 34 ± 2, respectively.

In a study examining the usefulness of a size-specific dose estimate in pediatric CT examination, Tsujiguchi et al. (2018) found that “when estimating the organ dose and effective dose for pediatric patients and the standard and thin body type patients, the SSDE-corrected value is less likely to underestimate the exposure dose than the conventional method using CTDI_volume and DLP, making SSDE a very effective method.”

Effective dose

The next stage in this area of patient dose assessment is to address the risk of a CT examination. This requires the use of the effective dose. Effective dose is used in radiation protection to relate exposure to risk, and it takes into account that different tissues have different radiosensitivities and the absorbed dose to specific organs. For example, the gonads are more radiosensitive than the brain (Bushong, 2017). Because only parts of the body (rather than the entire body) are exposed in medical diagnostic imaging, risk of stochastic radiation response is proportional to the effective dose rather than to the tissue dose. The effective dose is expressed by the following:

E = ∑T(WT  ⋅  WR  ⋅  DT,R)(10.9)

where W_T = tissue weighting factor, W_R = radiation weighting factor, and D_T,R = average absorbed dose to tissue T. The tissue and radiation weighting factors are available from tables provided by the ICRP and the NCRP.

The SI unit for E is the Sievert; whereas the old unit is the rem.

1Sv = 100 rem(1 rem = 10 mSv)

For simplicity, the effective dose is obtained by multiplying the DLP by constants referred to as k values, which have been previously established. For example, the k value (mSv/mGy-cm) for a CT scan of the head is 0.0021; the k value is 0.015 for a CT scan of the pelvis (McNitt-Gray, 2002). Knowing these k values enables calculation of the effective dose as follows:

ED = k × DLP(10.10)

The effective dose allows for a comparison of the dose received from CT scanning with the dose received from natural background radiation. For example, Bushong (2017) noted that while the annual effective dose from natural background radiation is reported to be 3 mSv, it is 1.5 mSv for CT and 3 mSv for medical imaging (CT scanning, radiography, and interventional, nuclear medicine).

Measuring the CT dose index

It is not within the scope of this book to describe the details of how to measure the CTDI because this is usually, a task for the medical physicist. However, the following steps are noteworthy, using the phantoms and pencil ionization chamber described earlier:

1. 1. The pencil ionization chamber is placed into one of the holes in the phantom, perpendicular to the fan of the radiation beam (i.e., the chamber is placed parallel to the longitudinal axis of the patient; see Fig. 10.5), and the other holes are plugged with acrylic plugs.
2. 2. An exposure is made for a single scan, and the chamber measures the exposure (not dose). The chamber intercepts the entire narrow width of the x-ray beam. The x-ray beam must be positioned in the center of the chamber.
3. 3. The chamber converts the x rays into charge. This charge represents the integral in Equation 10.2.
4. 4. The ionization chamber receives radiation from all parts of the dose distribution D(z) because of its length. The total charge from the ionization chamber is proportional to the integral in the CTDI definition. Mathematically, this is expressed as follows:

Q = 1Cf∫−∞+∞ D(z)  dz(10.11)

where Q is the total charge collected during a single scan and C_f is the calibration factor of the ionization chamber. Because the ionization chamber measures exposure and not the dose, a conversion factor (the f factor) must be included in C_f, which converts exposure (in Roentgens, R) to dose (cGy; recall that 1 cGy = 1 rad). The value of the f factor at CT scanner x-ray energies is approximately 0.94 cGy/R.

An interesting point to note about the CTDI is that the integration range is restricted to single-slice CT scanners collimated to beam widths of 10 mm and less (Boone, 2007) and to 100 mm for the CTDI₁₀₀. For example, the nominal beam width for the 256-slice CT scanner is 128 mm; therefore, the integration range has increased to 300 mm for an accurate measurement of the dose from this CT scanner.

Exposure technique factors

Exposure technique factors are characterized by the tube potential defined by the kilovoltage; tube current, defined by the milliamperage; and the exposure time in seconds. The product of the milliamperage and the exposure time is the milliamperage-seconds (mAs). The technologist can select these factors manually or they can be selected by using automatic exposure control (AEC), which uses a technique known as automatic tube current modulation and is described later in the chapter.

Effective milliamperage-seconds

The effective mAs is a term used for MSCT scanners that denotes the mAs per slice. This is given by the following relationship:

Effective mAs = True mAs/pitch(10.12)

This expression simply implies that, to keep the effective mAs constant, as the pitch increases, the true mAs must be increased as well. For example, increasing the pitch from, say, 1 to 2, increases the mAs per rotation from 100 to 200 while the relative CTDI_volume remains the same (Lewis, 2005).

Collimation (z-axis geometric efficiency)

In CT, the collimation is used to define the beam width for the examination. Collimation schemes are different between single-slice (single detector row along the z-axis) and MSCT scanners. The collimation reflects the efficient use of the x-ray beam at the detector, as shown in Fig. 10.12. The shaded portion represents the penumbra caused by the finite size of the x-ray tube focal spot. It is clearly apparent that on a single-slice CT scanner, the entire beam width plus the penumbra fall on the detectors. The penumbra, however, is not used to produce the image, but it does affect the patient dose.

On MSCT scanners, the beam width, including the penumbra, would fall on a finite set of detectors depending on the scanner, but the penumbra would not be used to produce the image (because the intensity of the beam at the penumbra regions is less than the intensity at the center of the beam). To address this problem, the beam width (collimation) is increased so that the penumbra extends beyond the active detectors that will receive the central beam intensity (Lewis, 2005). The ratio of the area under the z-axis dose profile falling on the active detectors to the area under the total z-axis dose profile is referred to as the z-axis geometric efficiency (IEC, 2001).

Cody and McNitt-Gray (2006) showed that for a 32-cm diameter phantom, as beam widths increase from 18.0 mm, 19.2 mm, 24.0 mm, and 28.8 mm, the CTDI_w (mGy) changes from 15.7 mGy, 16.8 mGy, 15.0 mGy, and 13.9 mGy, respectively (all other technical factors held constant). Additionally, Lewis (2005) indicated that “scanners that acquire a greater number of simultaneous slices have an advantage in terms of z-axis geometric efficiency. This is because for narrow slice widths a wider total collimation can be used. On multislice scanners z-axis geometric efficiencies are generally in the range of 80–98% for collimators of 10 mm and above, and about 55–75% for collimators of around 5 mm. For collimators around 1-2 mm z-axis geometric efficiencies are as low as 25% on some systems, although in dual slice mode, they can be much higher. Therefore, the reduced geometric efficiency of multislice scanners, for wider collimators most commonly used, leads to dose increases around 10% when compared with single slice systems. However, very narrow collimations can result in a tripling, or more, in dose”.

Pitch

The term pitch is one common to spiral/helical CT scanners, sometimes called spiral pitch or helical pitch, depending on the manufacturer of the scanner. As defined by the IEC, pitch is a ratio of the distance the table travels per rotation to the total collimated x-ray beam width. The relationship between the absorbed dose and pitch is as follows:

Dose ∝ l/pitch(10.13)

Therefore, if the pitch increases by 2, the dose will be reduced to one half. It is important, however, to note that this relationship only holds true when the pitch changes and all other factors remain constant. For constant mAs (100 mAs per rotation), if the pitch changes from 1 to 2, the relative CTDI_volume decreases from 1.0 to 0.5 mGy (Lewis, 2005).

Number of detectors

In a study comparing the dose from CT scanners, Moore et al. (2006) demonstrated that the measured radiation dose is inversely proportional to the number of detector rows. They showed that there is a trend that as the number of detector rows increases from 4 to 8 to 16 detector rows, the dose decreases with both standard and near identical technique.

Over-ranging (z-overscanning)

In spiral/helical CT scanning, it is important to realize that to image the planned length of tissue required for the examination and of interest to the radiologist, additional rotations before and after the planned length are essential for the image reconstruction process. This is referred to as over-ranging or z-overscanning (Tzedakis et al., 2007; Van der Molen and Geleijns, 2007), of which the components and definitions developed by Van der Molen and Geleijns (2007) are clearly illustrated in Fig. 10.13. It is clear that there are two definitions of over-ranging:

Over-ranging increases the dose to the patient, which is validated in studies conducted by Tzedakis et al. (2007) on pediatric patients and by Van der Molen and Geleijns (2007). For example, Tzedakis et al. (2007) concluded that “in all cases normalized effective dose values were found to increase with increasing z-overscanning. The percentage differences in normalized data between axial and helical scans may reach 43%, 70%, 36%, and 26% for head-neck, chest, abdomen-pelvis, and trunk studies, respectively.” Van der Molen and Geleijns (2007), for example, concluded that “overranging is reconstruction algorithm specific, and its length generally increases with collimation and pitch, while the effect of section width is variable. Over-ranging may lead to substantial but unnoticed exposure to radiosensitive organs.”

Patient centering

Another factor affecting the dose to the patient under the control of the technologist is that of patient centering. The patient must be centered in the gantry isocenter for accurate imaging of the anatomy. Inaccurate patient centering (miscentering or off-centering), as shown in Fig. 10.14, degrades the image quality and increases the dose to the patient, especially with the use of AEC in CT (Barreto et al., 2019; Euler et al., 2019; Isa et al., 2018; Saltybaeva et al., 2017). Additionally, the use of bowtie filters in CT scanners is intended to serve basically two purposes: to shape the beam intensity within the scan field of view (SFOV) and to produce a more uniform beam at the detectors (see Chapter 4). The x-ray beam is filtered; therefore, the bowtie filter actually plays a small role in reducing the dose to the patient because the low-energy photons are removed and thus the beam becomes harder, that is, the mean energy of the beam increases. Improper centering of the patient in the gantry isocenter as shown in Fig. 10.14 can lead to an increase in surface dose as well as the peripheral dose to the patient (Barreto et al., 2019; Euler et al., 2019; Isa et al., 2018; Saltybaeva et al., 2017). Furthermore, Kaasalainen et al., (2014) showed that miscentering was more pronounced in smaller pediatric patients, in terms of dose and image noise.

These findings are positive proof that technologists should always center the patient accurately in the gantry isocenter to avoid image noise problems and reduce the dose to the patient.

Automatic tube current modulation

AEC is now commonplace on CT scanners. AEC uses a technique referred to as automatic tube current modulation (ATCM) to optimize the dose to the patient while maintaining constant image quality, regardless of the size of the patient, in the z-axis and the attenuation changes in the x-y axis (McNitt-Gray, 2011; Supanich, 2013). ATCM has been hailed as “the most important technique for maintaining constant image quality while optimizing radiation dose” (Li et al., 2007), and especially in pediatric CT (Papadakis & Damilakis, 2019). For this reason, ATCM is described in detail in the next section.

Problem with setting manual milliamperage techniques

In CT, the exposure technique factors (mAs and kVp) do not have a direct effect on the image density and contrast, respectively (as they do in film-based radiography), because CT is a digital-imaging modality. The dose to the patient is directly proportional to the mA, and in the past, CT technologists selected the mA values for patients manually. Lewis (2005) explained one of the problems with setting the mA values manually. She noted:

the attenuation of the x-ray beam increases with the thickness of material in its path, and for approximately every 4 cm of soft tissue, the x-ray beam intensity halves. In order to achieve the same transmitted x-ray intensity, and thereby the same level of image noise, changing from a 16 cm to a 20 cm diameter phantom requires a doubling of the mA. Changing from a 32 cm to a 48 cm phantom, the mA should in theory, be increased by a factor of 16. Systems which automatically adapt the overall tube current based on actual patient attenuation remove the guesswork from selecting the appropriate mA setting.

Definition of automatic tube current modulation

In CT, automatic tube current modulation (ATCM) refers to the automatic control of the mA in two directions of the patient (the x-y axis and the z-axis) during data acquisition (scanning process) by use of specific technical procedures that take into consideration the patient size and the attenuation differences of the various tissues. The overall goal of ATCM is to provide consistent image quality despite the size of the patient and the tissue attenuation differences and to control the dose to the patient (Brisse et al., 2007; Li et al., 2007; McNitt-Gray, 2011; Supanich, 2013; Toth et al., 2007) compared with manual mA selection techniques. Although the automatic control of the tube current (mA) in the x-y axis (in-plane) is referred to as angular modulation, changing the tube current automatically in the z-axis (through-plane) is referred to as z-axis modulation or longitudinal modulation. When used together, that is, angular-longitudinal tube current modulation, AEC is the result (McNitt-Gray, 2011; Supanich, 2013).

The use of ATCM influences the dose to the patient and image quality (McNitt-Gray, 2011; Supanich, 2013). For example, Yurt et al., (2019) showed that “dose reductions of 31% and 21% were achieved by the ATCM protocol in the arterial and portal phases, respectively. On the other hand, NI exhibited an increase between 9% and 46% for liver, fat and aorta. CNR values were observed to decrease between 5% and 19%” (NI is an acronym of noise index set by the user and defines the level of image quality required for the examination. CNR refers to the contrast-to-noise ratio). The approaches for defining the level of image quality will be identified for four CT vendors later in the chapter.

Historical background

ATCM techniques can be traced back to 1981, when Haaga et al. (1981) suggested its use as a dose reduction strategy in CT that did not compromise the needed image quality to make a diagnosis. This was followed by efforts from General Electric (GE) Medical Systems in 1994 and researchers such as Kalender et al. (1999), who published two reports describing dose reductions as much as 40% with ATCM techniques (McCollough et al., 2006). Later in 2001, a number of CT manufacturers such as GE Healthcare, Philips, Siemens, and Toshiba introduced ATCM techniques referred to by several names.

Basic principles of operation

In CT AEC, the tube current (mA) is adjusted in real time during the scanning of a patient on the basis of differences in radiation attenuation in the transverse or x-y direction (in-plane) and the z-axis or longitudinal direction (through-plane) during the rotation of the tube and detectors. In addition, these tube current modulation techniques require some knowledge of the attenuation characteristics of the patient, and patient centering in the gantry is paramount (Kaasalainen et al., 2014). Furthermore, the operator must first set up the defined level of image quality (image noise target value) needed for the examination (Cody & McNitt-Gray, 2006; Lewis, 2005; McCollough et al., 2006). Each of these will be described briefly.

Longitudinal (z-axis) tube current modulation

Longitudinal (z-axis) tube current modulation (z-axis TCM) is based on differences in attenuation among body parts. For example, thicker body parts such as the abdomen and pelvis will attenuate the radiation more than thinner body parts, such as the head, neck, and chest regions. The technique of z-axis TCM is designed (using a specific computer algorithm) to change the mA automatically as the patient is scanned from, say, head to toe (along the z-axis) while maintaining a constant (uniform) noise level (image noise target values) for different thicknesses of body parts examined. This is clearly shown in Fig. 10.15.

Angular (x-y axis) tube current modulation

Angular (x-y axis) tube current modulation (x-y axis TCM) is based on the fact that the radiation attenuation varies from the anteroposterior (AP) projection (low attenuation) to the lateral projection (high attenuation) as the tube rotates around (gantry rotation) the patient. Although the high-attenuation projections will require higher mA values, the low-attenuation projections will require lower mA values, as illustrated in Fig. 10.16. The x-y axis TCM algorithm ensures that a constant (uniform) noise level is maintained during the scanning process.

Angular-longitudinal tube current modulation

Fig. 10.17 illustrates a method where both x-y axis and z-axis modulation can be used together to provide the “most comprehensive approach to CT dose reduction because the x-ray dose is adjusted according to the patient-specific attenuation in all three planes” (McCollough et al., 2006).

Biological effects of radiation exposure

Biological effects of radiation exposure were described previously. In summary, these effects fall into two broad categories: stochastic effects and deterministic effects. Stochastic effects are random, and the probability of their occurrence depends on the amount of radiation dose an individual receives. The probability increases as the dose increases, and there is no threshold dose for stochastic effects. Any amount of radiation, no matter how small, has the potential to cause harm. If harm occurs, the damage generally becomes apparent years after exposure; therefore, stochastic effects also are called late effects. Examples of stochastic effects include cancer and genetic damage (Bushong, 2017; Seeram & Brennan, 2017). Stochastic effects are considered a risk from exposure to the low levels of radiation used in medical imaging, including CT examinations.

Deterministic effects are those for which the severity of the effect (rather than the probability) increases with radiation dose and for which there is a threshold dose. Examples of deterministic effects include skin burns, hair loss, tissue damage, and organ dysfunction (Bushong, 2017). Deterministic effects are also referred to as early effects and involve high exposures that are unlikely to occur in medical imaging examinations.

Radiation protection philosophy

In diagnostic medical imaging, practitioners purposefully expose patients to a low dose of ionizing radiation as a means to improve or restore patients’ health. The goal of radiation protection is to prevent deterministic effects by ensuring that doses remain well below relevant threshold doses and to minimize the probability of stochastic effects.

To accomplish this goal, radiation protection in medical imaging is guided by international and national recommendations and frameworks such as those established by the International Commission on Radiological Protection (ICRP); and national radiation protection organizations such as the National Council on Radiation Protection and Measurements (NCRP); US Food and Drug Administration (FDA), and the Radiation Protection Bureau, Health Canada (RPB-HC), along with individual state guidelines and regulations.

The ICRP has provided three guiding principles of radiation protection (ICRP, 2007); namely, justification, optimization, and dose limitation. While the principles of justification and optimization address individuals who are exposed to radiation, the principle of dose limits deals with occupational and environmental exposures and excludes medical exposure. This subsection will only focus on the principle of optimization.

What is dose optimization?

Dose optimization is a radiation protection principle intended to ensure that doses delivered to patients are kept as low as is reasonably achievable (ALARA). The ultimate goal of optimization is to minimize stochastic effects and to prevent deterministic effects. The ICRP recommends approaches to dose optimization associated with radiography equipment and daily operations. While equipment optimization refers to the manufacturer’s design and construction of the imaging unit, operations optimization refers to the options radiologic technologists choose that enable them to follow the ALARA principle during the examination (ICRP, 2007). Optimization strategies also address image quality. Specifically, dose optimization strategies must not compromise the image quality required by physicians to diagnose diseases and conditions

Optimization strategies

As described earlier in this chapter, a number of factors affect the dose to the patient in CT. These include the scan parameters such as exposure technique factors (constant and effective mAs and kV), collimation (z-axis geometric efficiency), pitch, number of detectors, over-ranging (z-overscanning), patient centering, ATCM, and iterative and deep learning image reconstruction algorithms. In review, a brief summary of important CT dose parameters is provided in Table 10.2. To effectively reduce the dose and maintain the needed image quality parameters listed and defined in Table 10.3, users must have systematic approaches or strategies to accomplish the goals dose optimization.

In the past, several authors have described various dose optimization strategies in CT, especially in MSCT, that are not significantly different than more recent optimization strategies (Parakh et al., 2016; Smith-Bindman & Boone, 2014; Thakur et al., 2013). It is not within the scope of this chapter to describe details of these strategies; however, it is noteworthy to highlight a few essential guiding principles. Several strategies that emerge as common themes relate to the mAs, kV, collimation, slice thickness, scanned volume, pitch, and the use of ATCM techniques. A notable checklist for dose optimization is provided in Table 10.4.

Research on dose optimization and image quality¹

Dose optimization in CT based on image quality requires a thorough understanding of CT dose parameters and CT image quality parameters. CT image quality has been described in terms of high-contrast spatial resolution, low-contrast resolution, temporal resolution, CT number accuracy and uniformity, image noise, and image artifacts. Research has continued to determine the best methods for lowering radiation dose in CT examinations without compromising the diagnostic quality of images. These studies often are complex so they can follow precise scientific methods, including identifying the problem, performing a literature review, stating the goals regarding investigation of the problem, and designing a methodology to find a solution to the problem. Scientific methods also include data collection, analysis and interpretation of the data, and dissemination of the study findings.

In general, research on optimizing dose and image quality involves various methodologies to demonstrate dose reduction without a loss of image quality. To determine optimal image quality, McCollough et al. (2006) stressed that studies must involve quantitative metrics such as image noise and observer performance

In a special issue of the journal Radiation Protection Dosimetry dedicated to optimization strategies in medical imaging for fluoroscopy, radiography, mammography, and CT, several studies identified at least four important requirements for dose and image quality optimization research (Mattsson, 2005):

To accomplish these requirements, CT dose and image quality optimization studies should generally ensure that the following minimum essential elements are considered:

Receiving-operator characteristic is the most common observer performance method. Under this method, a study’s observers determine whether an image contains a lesion or pathology. The observer assigns a grade on a scale (e.g., 1 to 5) that rates the observer’s level of confidence in the decision (Tingberg et al., 2005).

A visual grading analysis assigns a grade to the image’s quality based on comparison with a reference image. Visual grading analysis is based on the assumption that an observer’s ability to see and evaluate normal anatomy correlates to the ability to evaluate pathology, or abnormal findings (Tingberg et al., 2005).

Radiation protection actions

Radiation protection actions include the use of time, shielding, and distance, which are intended to protect both patients and personnel in radiology. For example, because dose is proportional to the time of exposure, to protect personnel in CT, it is essential to minimize the time spent in the CT scan room during the exposure. Distance, on the other hand, is a major dose reduction action because the dose is inversely proportional to the square of the distance. This means that the further one is away from the radiation source, the less the dose received. In CT, because the patient is the main source of scatter, technologists should stand back as far away from the patient as possible if is necessary to be in the scan room during scanning. This implies that a power injector that can be controlled from outside the scan room is recommended. If a hand injector is used, then long tubing should be included.

Shielding is intended to protect not only patients (gonadal, breast, eyes, and thyroid) but also personnel and members of the public. Patients are often concerned about the exposure of their gonads during a CT examination. Because most of the gonadal exposure will come from internal scatter and not from the primary beam (unless the gonadal region was being examined), there is no need for this concern. Technologists, however, depending on the CT department policies, may place gonadal shielding on the patient because it may alleviate any fears about the risks of exposure to radiation. Shields can also be used to protect the eyes, breast, and thyroid of patients undergoing CT examinations. Bismuth shielding in CT has received some attention as to their effectiveness in offering protection, hence, the next section will provide a glimpse into the current state-of-the-art with respect to their use in CT.

Use of bismuth shield for protection of superficial radiosensitive organs

The use of bismuth (Bi) shields in CT has been discussed in recent literature reviews for protection of radiosensitive organs, most notably the breast, by attenuating the primary radiation beam from the x-ray tube (Lawrence & Seeram, 2017; Mehnati et al., 2019). Lawrence and Seeram (2017) found that “while bismuth shielding proves to provide significant dose reductions to radiosensitive organs, numerous concerns exist including wasted radiation, reduced image quality and unpredictable results when combined with AEC. Alternative methods such as tube current modulation and iterative reconstruction algorithms can provide equivalent dose savings at superior image quality, without the limitations of bismuth shields. Until these alternative methods become available in all departments, bismuth shielding remains a viable dose reduction strategy.”

The recent review by Mehnati et al. (2019) concluded that “the presence of a Bi shield was effective to decrease the patients’ surface radiation dose by decreasing the low-energy photons delivered at the surface. Comparison among the doses to the eye, thyroid, and breast showed that Bi shielding has potential for use in dose reduction, especially at the thyroid, without significantly lowering the image quality. Image quality, usage of foam, beam energies, and backscatter radiation were important factors that directly affected the efficacy of Bi shielding. The image noise assessed for imaging with and without Bi shield indicated that the increase in the noise level under Bi shielding was acceptable for making the diagnosis. Additionally, foam of optimum 1–2 cm thickness was recommended to decrease the noise in images acquired with bismuth shielding.”

The use of bismuth shields in CT discussed in the literature has sparked some debate among academics and practitioners, and various studies have shown advantages in dose reduction as well as problems imposed by these shields during the examination. This has led the AAPM to issue the following Position Statement on the Use of Bismuth Shielding for the Purpose of Dose Reduction in CT scanning (AAPM, 2014). The following statement is “policy text”:

“Bismuth shields are easy to use and have been shown to reduce dose to anterior organs in CT scanning. However, there are several disadvantages associated with the use of bismuth shields, especially when used with automatic exposure control or tube current modulation. Other techniques exist that can provide the same level of anterior dose reduction at equivalent or superior image quality that do not have these disadvantages. The AAPM recommends that these alternatives to bismuth shielding be carefully considered, and implemented when possible.”

The AAPM also provides a description of the reason for this policy, and lists the following disadvantages of using bismuth shields. These include:

Furthermore, the AAPM also provides “Alternative methods for reducing dose to peripheral organs in CT scanning” and lists 14 references of relevance to the use of bismuth shielding in CT. The interested reader should refer to this AAPM document.

In order to improve the performance of bismuth shields in terms of dose reduction in CT,

Noor Azman et al. (2016) and Abunahel et al. (2018) applied bismuth oxide (Bi₂O₃) nanoparticles (instead of micro particles) and silicone rubber to make a nano bismuth shield to improve the efficiency of the shield in reducing the radiation dose to radiosensitive organs. Subsequently, Mehnati et al. (2020) showed that the nano Bi₂O₃ shield (instead of micro bismuth shield) with 1mm thickness, reduced the dose by about 15% higher. Furthermore, the noise increase in nano Bi₂O₃ shields was equal to 14%, which is less than the micro bismuth shield. They concluded that “the nano bismuth composite shield with different ratios and thicknesses show significant dose reduction in the breast. This could play a role in breast cancer prevention during chest CT scan.”

In yet another study examining the quantification of CT numbers (CTN) and the contrast-to-noise ratios (CNRs) “for five tissue-mimicking materials for bismuth shields of different thicknesses and for positions relative to these shields during CT scans” and dose reduction for different thicknesses of bismuth shields, Liao et al. (2019) found that “using a bismuth shield could result in significant CTN changes and perceivable artefacts, particularly for a superficial organ close to the shield, and is not recommended for quantification CT examinations or follow-up CT examinations.”

Definition

The term diagnostic reference level (DRL) was first introduced by the ICRP in 1990, and subsequently explained in more detail in 1996, and updated in 2017 (ICRP, 2017). In this updated publication, the ICRP recommends the use of the following:

“A DRL is a form of investigation level used to aid in optimisation of protection in the medical exposure of patients for diagnostic and interventional procedures. A DRL value is a selected level of a DRL quantity for broadly defined types of equipment for typical examinations for groups of patients within an agreed weight range or, in certain specific circumstances, a standard phantom. DRLs do not apply to individual patients. They are derived as an arbitrary threshold from radiation metric data obtained locally and collected nationally or regionally. A DRL is a supplement to professional judgement and does not provide a dividing line between good and bad medical practice. All individuals who have a role in subjecting a patient to a medical exposure should be familiar with DRLs as a tool for optimisation of protection.”

DRLs are now used globally and have been endorsed by various organizations such as the ICRP, the American College of Radiology (ACR), the AAPM, United Kingdom Health Protection Agency, International Atomic Energy Agency, and European Commission (Seeram & Brennan, 2017). There are several reasons why it is important to implement DRLs. It is not within the scope of this chapter to outline these reasons in any detail; however, it is noteworthy that these reasons address legal or regulatory requirements, societal benefits, and improved awareness of radiation doses (Seeram & Brennan, 2017).

Establishing DRLs

There are several steps to establishing DRLs (ICRP, 2017; Seeram & Brennan, 2017). First, DRLs must be relevant to the state or country where they are applied. To be relevant, DRLs are determined from radiation dose survey data. The aggregate data from these surveys represent all hospitals in a particular region or state. Dose surveys should be performed by hospitals continuously or at least regularly carried out in three to five consecutive annual intervals. DRLs should be considered a dynamic and changing parameter so that they are always applicable to examinations performed or to new hospital equipment.

When planning a dose survey, a number of parameters should be considered: examination type, number and type of hospitals involved, phantom investigations, patient investigations, dosimetry methods, establishment of the reference level, and accessory information. These parameters will not be described here; however, the interested reader may refer to the ICRP Report 135 (2017) or to Seeram and Brennan (2017).

Setting DRL values

Fig. 10.18 illustrates hypothetical data collected from a survey of 17 hospital CT scanner rooms showing the doses (mGy) delivered for an AP lumbar spine projection. The dose values were arranged in increasing order. The next step is to establish DRLs. In this regard the ICRP (2017) recommends that “the median value (not the mean value) for the DRL quantity from each of the facilities in the survey should be used,” and that national DRL values should be set as the 75th percentile (see Fig 10.18). This value becomes the reference level. It is clear from Fig. 10.18, that four hospitals are above this level. This means that the four hospitals above this level need to engage in radiation protection activities that would bring the dose levels below the 75th percentile. For a thorough description of setting DRL values, the interested reader should refer to the ICRP Report 135 (ICRP, 2017).

The ACR DRL benchmarks for patient-based adult CT were established using the CTDI_volume, SSDE, and the DLP from the ACR’s Dose Index Registry. For example, the DRLs for chest without contrast, are 12 mGy (CTDI_volume); 15 mGy (SSDE); and 443 mGy-cm (DLP), while the achievable doses (AD) are 9 mGy (CTDI_volume); 11 mGy (SSDE); and 334 mGy-cm (DLP). For the abdomen and pelvis without contrast, for example, the DRLs are 16 mGy (CTDI_volume); 19 mGy (SSDE); and 781 mGy-cm (DLP), while the ADs are 13 mGy (CTDI_volume); 15 mGy (SSDE); and 639 mGy-cm (DLP) (ACR, 2018).

What is the dose index registry?

The ACR (https://www.acr.org/Practice-Management-Quality-Informatics/Registries/Dose-Index-Registry) describes the dose index registry (DIR) as a data registry that:

“....lets facilities compare their CT dose indices to regional and national values. They receive quarterly feedback reports comparing their results to aggregate results by body part and exam type.”

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