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Improving CT quality with optimized image parameters for radiation treatment planning and delivery guidance

Open AccessPublished:November 08, 2017DOI:https://doi.org/10.1016/j.phro.2017.10.003

      Abstract

      Background and purpose

      CT scan protocols are often created with imaging parameters set to minimize imaging dose with acceptable image quality for diagnostic purpose. This study aimed to optimize CT imaging parameters to help accurately delineate structures for radiation therapy planning and delivery guidance.

      Materials and methods

      Imaging parameters were optimized with CT data acquired for a phantom to create image quality enhancement (IQE) protocols, which were subsequently used to scan a prostate and a pancreatic cancer patient who underwent image-guided radiotherapy (IGRT). The patient images were compared with those scanned with standard clinical protocols, the quality of these images was assessed with various methods (survey, inter- and intra-observer variations, and dice coefficient analysis) for the two patient cases.

      Results

      An effective tube current–time product of   ∼1000 mAs was found to be a reasonable choice to balance CT quality and CT dose. With increased dose and penetration taken into account, 100 and 120 kV tube voltages were found appropriate for the IQE protocols. The inter- and intra-observer variations for the IQE data were smaller than those with the standard protocols. Dice coefficient analysis indicated that the IQE protocols lead to improved dice coefficient by as much as 8 percentage points for the two cases studied.

      Conclusion

      CT image quality can be improved with the IQE protocols created in this study, to provide better soft tissue contrast, which would be beneficial for use in radiation therapy, e.g., for planning data acquisition or for IGRT for hypo-fractionated treatments.

      Keywords

      1. Introduction

      Computed tomography (CT) has been widely used in diagnostics and radiotherapy (RT). Dose from CT imaging has an associated risk and should be kept low [
      • Brenner D.
      Induced cancers after prostate-cancer radiotherapy: no cause for concern?.
      ]. For diagnostic purposes, CT dose is often minimized as long as CT quality is acceptable [
      • Kalra M.K.
      • Maher M.M.
      • Toth T.L.
      • et al.
      Strategies for CT radiation dose optimization.
      ]. For RT, CT has been used mainly for RT planning (RTP) and, in recent years, for guiding RT delivery, e.g., image guided radiotherapy (IGRT). High CT quality is essential for accurate 3D structure delineation in both RTP and IGRT. Consequently, goals for using CT in diagnostics and RT are different. As Hevezi pointed out, CT scan protocols should be adjusted to obtain sufficient CT image rendition for the planning procedure at hand [
      • Hevezi J.M.
      • Mahesh M.
      Optimizing CT dose and image quality for radiotherapy patients.
      ]. This may require an actual increase in CT scan technique from that used for reduced-dose diagnostic techniques. The CT acquisition protocols that are often optimized for diagnostic radiology (often provided by vendors) may not be optimal for RT. The ultimate goal of RT is to deliver a high dose of radiation to a tumor while sparing the surrounding normal tissues as much as possible. In RTP, it is a common practice to add a margin surrounding gross tumor volume (GTV) to form clinical target volume (CTV), and to add another margin surrounding CTV to create planning target volume. These margins are introduced to account for various factors, including structure delineation uncertainties. It is highly desirable to reduce these margins for the purpose of reducing radiation dose to organs at risk. On the other hand, IGRT may have limited clinical value due to lack of accurate structure delineation [
      • Njeh C.F.
      • Dong L.
      • Orton C.G.
      IGRT has limited clinical value due to lack of accurate tumor delineation.
      ]. Thus, improving CT quality to reduce structure delineation uncertainty in RTP and to reduce alignment error in IGRT is helpful and crucial for a successful treatment.
      Therefore, in radiation oncology, an increase in CT dose in exchange for improved CT quality may be justified. The CT dose may be negligible in comparison to the therapeutic dose. In particular, for some special procedures, such as stereotactic body radiotherapy (SBRT), the dose increase from CT scan, as compared to the prescription dose, can be acceptable. Based on phantom studies, Li et al. developed a general strategy to predict the optimal CT simulation protocols in a flexible and quantitative way that takes into account patient size, treatment planning task, and radiation dose [
      • Li H.
      • Yu L.
      • Anastasio M.A.
      • et al.
      Automatic CT simulation optimization for radiation therapy: a general strategy.
      ]. They defined an image quality index (IQI) to act as a surrogate linking the optimal simulation protocol to the contouring and treatment planning task. Their study indicated that the optimal CT simulation protocol and the corresponding radiation dose varied significantly for different patient sizes, contouring accuracy, and radiation treatment planning tasks. Furthermore, alternative CT modalities with higher CT doses, such as megavoltage CT or cone beam CT have been commonly used in IGRT. By increasing the linear accelerator (LINAC) pulse rate, Westerly et al. studied high-dose imaging modes on a clinical tomotherapy machine [
      • Westerly D.C.
      • Schefter T.E.
      • Kavanagh B.D.
      • et al.
      High-dose MVCT image guidance for stereotactic body radiation therapy.
      ]. They concluded that increasing the imaging dose results in increased contrast-to-noise ratio (CNR), and makes it easier to distinguish the boundaries of low contrast objects. The American association of physicists in medicine (AAPM) has recommended that [
      • Murphy M.J.
      • Batler J.
      • Batler S.
      • et al.
      The management of imaging dose during image-guided radiotherapy: report of the AAPM Task Group 75.
      ], in IGRT, minimizing CT dose must be within a context of relative cost versus benefit that will vary from patient to patient. CT imaging parameters, including tube voltage (kV), tube current (mA) and rotation time, slice thickness, and pitch, may be adjusted to optimize image quality versus radiation dose. IGRT with in-room CT imaging which offers diagnostic CT image quality has been used in practice for online adaptive therapy [
      • Ahunbay E.
      • Peng C.
      • Chen G.P.
      • et al.
      An on-line replanning scheme for interfractional variations.
      ]. However, extra time spent on structure delineation for re-planning after image acquisition is still one of the major problems that make online adaptive therapy not quite practical. Better image quality would help reducing the time needed for the structure delineation. Similarly, for IGRT treatments, any reduction in time spent for patient image registration verification would help the ultimate treatment delivery accuracy. The purpose of this study was to create a simple protocol for in-room CT imaging that improves CT quality by optimizing CT acquisition and reconstruction parameters including increasing CT dose if necessary for IGRT/treatment verification as well as treatment planning (including adaptive re-planning) in radiation therapy.

      2. Materials and methods

      2.1 General strategy

      Images scanned with low dose protocols would introduce inaccuracy in contouring which would lead to inadequate target coverage or excess dose to organs at risk. However, if the image noise is small enough so that the contouring error from imaging is not the main contributing factor, further increase of the image dose is not necessary. Therefore, for either treatment planning or IGRT, accurately delineating structures is our key indicator for the optimal protocol. Delineating accuracy is related to the image contrast and noise level. Contrast on the CT images was determined as the difference in CT numbers between two materials [
      • Boone J.M.
      • Geraghty E.M.
      • Seibert J.A.
      • Wootton-Gorges S.L.
      Dose reduction in pediatric CT: a rational approach.
      ]. The CNR [
      • Yan H.
      • Cervino L.
      • Jia X.
      • Jiang S.
      A comprehensive study on the relationship between the image quality and imaging dose in low-dose cone beam CT.
      ,
      • Xu J.
      • Reh D.D.
      • Carey J.P.
      • Mahesh M.
      • Siewerdsen J.H.
      Technical assessment of a cone-beam CT scanner for otolaryngology imaging: image quality, dose, and technique protocols.
      ] was defined as the ratio of the contrast, which is the difference of mean CT numbers between the two regions of interest (ROI), and the average of standard deviations of CT numbers in the two ROIs:
      CNR=2|μS-μB|σS+σB,


      where μS and μB are the average CT numbers in the signal and background ROIs, and σS and σB are the standard deviations of CT numbers in the signal and background ROIs, respectively. To take radiation dose into consideration, a dose-weighted CNR is defined as [
      • Kalender W.A.
      • Deak P.
      • Kellermeier M.
      • van Straten M.
      • Vollmar S.V.
      Application- and patient size-dependent optimization of x-ray spectra for CT.
      ,
      • Lee S.W.
      • Kim H.J.
      • Kim D.H.
      • Lee C.L.
      Evaluation of dose reduction and image quality in pediatric multi-detector CT.
      ]:
      CNRD=CNRD.


      The maximum CNRD represents the minimum dose value for a given image quality level. Optimization is achieved with a maximum CNRD. In this study, we used phantom data to find the optimal scanning parameters for our scan protocol. The protocol was then used on patients. Patient scan data were analyzed to verify better contouring accuracy was achieved.
      All CT data were acquired with a CT scanner (Somatom Definition AS Open, Siemens) installed inside a LINAC room (i.e., CT-on-rails). The CT scanner has the Automatic Exposure Control capability, known as CARE Dose4D [

      Flohr T. CARE Dose 4D. White Paper (Siemens Healthcare) 2011; A9115–111236-C1-4A00.

      ]. With CARE Dose4D, the user sets adaptation strength, selects a tube voltage (kV) setting and determines a quality reference tube current–time product (mAs). A topogram is performed prior to the actual scans to determine tube current values at different angular and axial positions so that patient size and attenuation changes can be adapted.

      2.2 Phantom measurements

      To find a balance between image quality and imaging dose, a CatPhan 500 phantom (Phantom Laboratory) which is 20 cm in diameter and includes a high spatial resolution module (CTP528) consisting of a 1 through 21 line pair per centimeter test gauge as well as a low contrast module (CTP515) consisting of supra-slice and sub-slice contrast targets was scanned with coaxial setups. CARE Dose4D was not turned on for image acquisition with this phantom because CARE Dose4D has no current modulation effect over coaxial cylindrical objects. Scans were acquired with rotation time of 0.5 s, slice thickness of 3 mm, pitch of 0.6, and the maximum available effective tube current–time product with each of the following tube voltage settings: 70 kV (415 mAs), 80 kV (541 mAs), 100 kV (541 mAs), 120 kV (514 mAs), and 140 kV (451 mAs). The scans were repeated five times and then averaged to simulate high mAs scans which cannot be achieved due to machine limitation [
      • Hulme K.W.
      • Rong J.
      • Chasen B.
      • et al.
      A CT acquisition technique to generate images at various dose levels for prospective dose reduction studies.
      ].
      After phantom data were acquired, the raw data were reconstructed with different reconstruction algorithms. The reconstructed images of the CTP 528 high spatial resolution module from all different tube voltage and effective tube current–time product settings were reviewed by five experienced medical physicists. There is a tradeoff between spatial resolution and noise for each reconstruction kernel. A smoother kernel generates images with lower noise but with reduced spatial resolution. A sharper kernel generates images with higher spatial resolution, but increases the image noise. The selection of reconstruction kernel should be based on specific clinical applications [

      Computed Body Tomography with MRI Correlation, 4th Edition, Volume 1, edited by Joseph K. T. Lee, Lippincott Williams & Wilkins, 2006. 1821p.

      ]. For our purpose, we reconstructed the CT images of the CTP 528 high spatial resolution module in the CatPhan 500 phantom with various reconstruction kernels, and selected the first kernel (from smoother to sharper) with reconstruction images where a 5 line pair (5/cm) in the module could be clearly seen in all reconstructed images. To calculate CNR, two ROIs were drawn with the signal ROI inside the 15 mm diameter target in the 1% contrast level of the supra-slice in the CTP515 module, and the background ROI outside but next to the target without overlap over any other target in the CTP515 module. To determine the appropriate tube voltage, the CNR, the increased dose, as well as penetration was considered.
      In the meantime, in each phantom image, a circular ROI in the uniform region was created and the CT numbers in the ROI were binned into a histogram. The distribution of the noise in uniform regions of the phantom was fit by a Gaussian. With the CatPhan 500 scan images at different effective tube current–time product levels, the relationship between noise and the effective tube current–time product was determined. The relationship was then used to simulate noise at certain effective tube current–time product levels and the images with artificially generated noise were compared against CatPhan 500 images that were taken later at the corresponding effective tube current–time product.

      2.3 Application of the protocol on patients

      The optimal parameters were obtained based on an analysis of the phantom data. Image quality enhancement (IQE) protocols were then created based on the optimized parameters. The IQE protocols suitable for prostate and pancreas were used to acquire patient data at these two tumor sites for one daily IGRT scan per patient with the CT-on-Rails. Higher tube voltage may be chosen in the IQE protocol for pancreas patient to reduce the appearance of streaking artifacts caused by a metal stent that usually exists in pancreas patients. Patient consent was obtained. The image quality of the patient CTs acquired with IQE protocols was compared with that obtained with standard clinical protocols. An image pair, obtained from the standard clinical and IQE protocols, was compared by surveying thirty radiation oncology staff including radiation oncologists, medical physicists, dosimetrists, and radiation therapists. The participants were asked to visually identify the better image in terms of structure boundary and spatial resolution without knowing the difference between the two. The comparison was also performed by evaluating the structure delineation consistency by either (1) manual contouring of ten observers (two radiation oncologists, two medical residents, two physicists, two dosimetrists and two therapists), or with (2) an in-house deformable registration tool.
      In method (1), contours for relevant structures (bladder, prostate and rectum for prostate patient, duodenum and pancreas head for pancreas patient) were drawn on the two sets of CT images in two scenarios: (a) drawn ten times by one user (intra-observer) with one set of contours drawn a week after the previous set, and (b) drawn one time per participant by all ten observers (inter-observer). The variations between the contours for a given organ were then compared by calculating the ratios of the standard deviation of volumes to the average of the volumes of the contour. The average time spent on contouring one data set for all individual users was also compared for the image data sets acquired with the standard clinical and IQE protocols.
      The purpose of method (2) was to find out if the IQE protocol can improve image registration. The CT images acquired with the standard clinical and IQE protocol during daily IGRT were registered to the planning CT acquired with the standard clinical protocol based on deformable image registration using an in house tool based on a systematic force Demons algorithm and a novel variable kernel smoothing technique [
      • Hart V.
      • Chen G.P.
      • Li X.A.
      The effect of CT image quality on deformable image registration in radiotherapy.
      ]. Contrast enhancement [
      • Ritika Kaur S.
      Contrast enhancement techniques for images-a visual analysis.
      ] and histogram matching [
      • Coltuc D.
      • Bolon P.
      • Chassery J.M.
      Exact histogram specification.
      ] were used to further compensate for intensity differences between the CT sets acquired with different protocols. Registration accuracy was then determined using the Dice similarity coefficient [
      • Allozi R.
      • Li X.A.
      • White J.
      • et al.
      Tools for consensus analysis of experts’ contours for radiotherapy structure definitions.
      ] to measure the overlap of planning and daily contours.
      As it is not practical to scan patients with a variety of effective tube current–time product settings, we made an effort to simulate patient CT scans with different tube current–time product values by adding artificially generated noise to the IQE protocol CT images. A Matlab routine was written that generates noise using a random number generator. The relationship between noise and the effective tube current–time product was determined from the phantom data. The CT scans of the CatPhan 500 provided the noise amplitude, standard deviation, and noise power spectrum as a function of effective tube current–time product. The Matlab routine then extrapolated the observed noise properties into the desired imaging dose levels. Furthermore, a multi pixel smoothing was applied to the simulated noise in order to account for the observed noise texture. Once the noise model was set, it was applied to the question of optimal dose for the IQE protocol. The model was validated with additional phantom scans. The improvement of CT quality can be measured by the ability to distinguish an edge between two organs in the body. The sharpness of the change in contrast as measured by the gradient is what makes an edge visible. The lower the contrast between two organs the more difficult it is to delineate an edge, yet a low contrast edge can be distinguished if the gradient is sufficiently high. Noise in the image degrades the gradient and hence the visibility of an edge. For our purposes, a useful test subject was the edge between the prostate and the bladder for the prostate patient.

      3. Results

      3.1 Determination of optimal protocol and noise model based on phantom data

      The reconstruction kernel B31s was found to be the first sharper kernel with which the 5 line pair was all clearly seen in the reconstructed images, and it was used in all phantom image reconstruction. The CNRs for the target in CatPhan images with different imaging parameters were obtained. The CNRs increase with effective tube current–time product (Fig. 1a). Although not obvious, a weak trend with the CNRD beginning to drop near 1000 mAs was seen (Fig. 1b). Based on these, we determined that an effective tube current–time product of 1000 mAs was appropriate, because the dose weighted CNR, namely CNRD, started to decrease or plateau. As a result of compromise, a tube voltage setting of 100 kV was optimal, but 120 kV was used for pancreas patient as explained previously.
      Figure thumbnail gr1
      Fig. 1Variation of CNR (a) and CNRD (b) for the CatPhan 500 versus effective tube current–time product for different tube voltages. (c) The obtained relationship between noise and the effective tube current–time product. (d) The CT number histograms (with mean CT number subtracted) from both simulation and phantom scan images at effective tube current–time product of 100 mAs. The histograms were both normalized to the total counts.
      It was determined that the noise in uniform regions of the phantom was very well fit by a Gaussian which simplified the noise model. The relationship between noise and the effective tube current–time product determined is shown in Fig. 1c. We tested the model by rescanning the phantom. Fig. 1d shows the CT number histograms from both simulation and phantom scan images at effective tube current–time product of 100 mAs. It was seen that the simulated noise spectrum was matched to the noise spectrum shape as measured in the CatPhan 500 scans.

      3.2 Comparison of patient data with old and new protocols

      IQE protocols for patient scans were created based on phantom data. Sample IQE protocols suitable for prostate and pancreas scans were compared with the standard clinical protocols in Table 1. The main differences between the standard clinical and IQE protocols were that the effective tube current–time product was increased to 1000 mAs, CareDose4D was turned on, the rotation time was increased from 0.5 s to 1.0 s, and the reconstruction algorithm was changed from B10f to B31s based on the phantom data and was verified with patient image data. Increasing rotation time allowed for larger effective tube current–time product to be used so that a patient scan of 1000 effective mAs could be performed in one scan.
      Table 1Imaging parameters for standard clinical and IQE protocols.
      ParameterStandard clinical protocolIQE protocol
      ProstatePancreas
      Tube voltage (kV)120100120
      Effective tube current–time product (mAs)21010001000
      CareDose4DOffOnOn
      Rotation time (s)0.51.01.0
      Pitch0.60.60.6
      Slice thickness (mm)333
      Reconstruction algorithmB10fB31sB31s
      Typical CTDIvol (mGy)175084
      Visual inspection of the CT images obtained with IQE protocol demonstrated improved visibility of the prostate gland boundary. An image pair, obtained from the standard clinical and IQE protocols, was shown in Fig. 2. A majority of the survey participants (twenty seven out of thirty) indicated that the image produced with the IQE protocol was better. The averaged reduction of time for contouring bladder, prostate and rectum on images acquired with the IQE protocol compared with that on images acquired with the standard clinical protocol was ∼ 10%. For intra-observer variation, the IQE protocol yielded smaller variations for all three structures for the prostate cancer case (Fig. 2c). For the inter-observer variations, the ratios for both prostate and bladder were smaller for the IQE protocol; however for the rectum the ratio was slightly higher for the IQE protocol in comparison to the standard clinical protocol (Fig. 2d). This exception may be partially explained by the substantial differences in the shape and volume of the rectum between the two days. The Dice coefficients for the registration of CT images from IQE protocol with planning CT images were found to be slightly larger than those for the registration of CT images from the standard clinical protocol with the same planning CT, e.g., by 3.3 percentage point (pp) for bladder, 1.0 pp for prostate, and 1.1 pp for rectum, indicating again that the IQE protocol improved CT quality for IGRT. The above results for improved registration with the IQE protocol were further examined by assessing the enhanced edge delineation due to noise reduction. Fig. 3 shows a sample image (b) with artificial noise level corresponding to 500 mAs, which was compared with the CT images acquired with the standard clinical (a, 210 mAs) and IQE (c, 1000 mAs) protocols. As a measure of the image quality in these three images, we extracted the CT numbers in a strip of voxels that cross the boundary between the prostate and bladder (the vertical line as shown in Fig. 3b). Plots of the voxel location versus CT number are presented in Fig. 3d for the three CT sets. It was seen that as the effective dose increases, the noise is reduced and it has the tendency that the CT number has higher gradient at the location of the edge. Thus, the higher effective dose CT achieves a meaningful enhancement in the delineation of structures.
      Figure thumbnail gr2
      Fig. 2Sample images scanned with standard clinical (a) and IQE (b) protocols for a prostate cancer patient. Contour variation (ratios of standard deviation over average of structure volumes) for the same patient: intra-observer (c) and inter-observer (d).
      Figure thumbnail gr3
      Fig. 3A sample image (b) with noise level corresponding to 500 mAs, which was compared with the CTs acquired with the standard clinical (a, 210 mAs) and IQE (c, 1000 mAs) protocols. The line in (b) represents a strip of voxels which illuminate the gradient between prostate and bladder as described in the text. (d) The CT number crossing the boundary in images acquired with the IQE protocol (High), the standard clinical protocol (Low) and the simulated image generated from adding noise to the IQE protocol (Adjusted).
      The same comparisons were also made for a pancreatic cancer patient. Visual inspection also indicated that the quality of the image scanned with the IQE protocol was improved over the image scanned with the standard clinical protocol. The dice coefficients for pancreas were calculated for 5 slices. The average improvement in the registration was 8.5 pp from the CT images with the standard clinical protocol to those with the IQE protocol.

      4. Discussion

      In this study, we created IQE protocols based on phantom measurements and applied them with patient scans to improve image quality. Whilst most other studies focused only on either treatment planning contours or IGRT, we considered treatment planning contours for both initial planning and online adaptive replanning purposes, as well as IGRT. Therefore, time for structure delineation and image registration was also one of our concerns, and we did not use treatment plan quality as a metric for the image quality but used the CNRD response with effective tube current–time product instead. The study by Li et al proposed and implemented a general strategy for automatic CT simulation technique selection for radiation therapy by using the IQI which was defined to characterize the simulation performance on structure delineation and used to benchmark the contouring accuracy and treatment plan quality [
      • Li H.
      • Yu L.
      • Anastasio M.A.
      • et al.
      Automatic CT simulation optimization for radiation therapy: a general strategy.
      ]. Our study focused more on the treatment delivery accuracy and was not intended for individual patient. This is because for treatment delivery, setup time is often limited; protocol adjustment per patient is subject to human error. Unlike Westerly et al.’s study, we used in-room CT scanner which provides diagnostic level image quality and could benefits treatment planning and both online and offline adaptive therapy also.
      Optimization of imaging is one of the three major areas that could contribute to improving the accuracy of structure delineation in addition to implementation of standardized delineation protocols and guidelines, as well as specialized training [
      • Segedin B.
      • Petric P.
      Uncertainties in target volume delineation in radiotherapy-are they relevant and what can we do about them?.
      ]. While the latter two are not in the scope of our discussion, image quality improvement can be achieved with new imaging techniques such as MRI, PET-CT, and functional MRI that improve visibility of the target. Potential advantages of functional imaging modalities are reduction of inter-observer variability, identification of tumor extensions missed by CT and/or MRI and possibly identification of GTV subvolumes requiring higher radiation dose. However, most of the current IGRT techniques are still CT based. Our study showed evidence that the inter-observer variability could be reduced with improved image quality by using the IQE protocols.
      The use of IQE protocols on patient scans showed some improvement in image quality over a standard clinical protocol. However, the imaging dose, based on CTDIvol, to patients with an IQE protocol was about three to five times of that with the standard clinical protocol, namely, about 50–84 mGy per scan. Increasing imaging dose to improve image quality must be weighed against the risks associated with additional exposure to the patient (especially for pediatric patients). As Westerly et al. pointed out [
      • Westerly D.C.
      • Schefter T.E.
      • Kavanagh B.D.
      • et al.
      High-dose MVCT image guidance for stereotactic body radiation therapy.
      ], assessing the risks posed by imaging is difficult because the risks that come with the additional radiation exposure (e.g. to bladder and rectum for prostate patients) are offset by the potential benefits of early detection (in the case of diagnostic x-ray imaging) and more precise targeting (in the case of treatment planning and IGRT). The three steps to manage imaging dose recommended by AAPM TG75 [
      • Murphy M.J.
      • Batler J.
      • Batler S.
      • et al.
      The management of imaging dose during image-guided radiotherapy: report of the AAPM Task Group 75.
      ] can be followed: (1) assessment, (2) reduction, and (3) optimization. If the IQE protocol is used for all fractions of a prostate patient with conventional fractionation, the CT dose would be a little bit over 3 Gy which would be significant as compared to the prescription dose, and therefore it might not be suitable for daily IGRT for a standard treatment plan. However, if IQE protocol is used instead of standard clinical protocol for treatment planning CT acquisition (∼7 cGy extra CT dose), for online adaptive replanning together with IGRT use (∼7 cGy extra each time for 2–3 times in the course of treatment depending on patient anatomy change), for weekly IGRT (∼35 cGy extra), or for hypo-fractionated treatment such as SBRT treatments delivered in three to five fractions (∼35 cGy extra), the dose increase as compared to the prescription dose would be acceptable.
      CT protocols can be optimized for radiation therapy planning and delivery by considering specific situations including tissue types (electron densities) and tumor sites (e.g., body thickness). When all factors are considered, tube voltage of 100 or 120 kV and effective tube current–time product of 1000 mAs were found to be the appropriate choices for scanning abdomen and pelvis. The CT image quality with IQE protocols was improved comparing to those using the standard clinic protocols. The imaging dose with the IQE protocol would be approximately three to five times of that with the standard clinic protocols, which may be justified for RT, particularly for RT planning, online adaptive RT and SBRT.

      Conflict of interest

      The authors whose names are listed immediately below certify that they have NO affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. Guang-Pei Chen George Noid An Tai Feng Liu Colleen Lawton Beth Erickson X. Allen Li.

      Acknowledgement

      This study was supported in part by Medical College of Wisconsin Cancer Center Fotsch Foundation and by Siemens Medical.

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      • Erratum regarding previously published papers
        Physics and Imaging in Radiation OncologyVol. 13
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          The Publisher would like to point out that the papers listed below were mistakenly published without Declaration of Interest statements. Statements have now been added to each paper and are also gathered below within this erratum.
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