CT Protocol Optimization Research Articles

Development of software helping in optimizing computed tomography protocols: Initial results

Introduction: A simulation tool was developed to enable the visualization of the effect of CT protocol optimization on Image Quality (IQ) and radiation dose.

SU‐F‐18C‐01: Minimum Detectability Analysis for Comprehensive Sized Based Optimization of Image Quality and Radiation Dose Across CT Protocols

Purpose:This work involved a comprehensive modeling of task‐based performance of CT across a wide range of protocols. The approach was used for optimization and consistency of dose and image quality within a large multi‐vendor clinical facility.Methods:150 adult protocols from the Duke University Medical Center were grouped into sub‐protocols with similar acquisition characteristics. A size based image quality phantom (Duke Mercury Phantom) was imaged using these sub‐protocols for a range of clinically relevant doses on two CT manufacturer platforms (Siemens, GE). The images were analyzed to extract task‐based image quality metrics such as the Task Transfer Function (TTF), Noise Power Spectrum, and Az based on designer nodule task functions. The data were analyzed in terms of the detectability of a lesion size/contrast as a function of dose, patient size, and protocol. A graphical user interface (GUI) was developed to predict image quality and dose to achieve a minimum level of detectability.Results:Image quality trends with variations in dose, patient size, and lesion contrast/size were evaluated and calculated data behaved as predicted. The GUI proved effective to predict the Az values representing radiologist confidence for a targeted lesion, patient size, and dose. As an example, an abdomen pelvis exam for the GE scanner, with a task size/contrast of 5‐mm/50‐HU, and an Az of 0.9 requires a dose of 4.0, 8.9, and 16.9 mGy for patient diameters of 25, 30, and 35 cm, respectively. For a constant patient diameter of 30 cm, the minimum detected lesion size at those dose levels would be 8.4, 5, and 3.9 mm, respectively.Conclusion:The designed CT protocol optimization platform can be used to evaluate minimum detectability across dose levels and patient diameters. The method can be used to improve individual protocols as well as to improve protocol consistency across CT scanners.

CT Protocol Review and Optimization

To reduce the radiation dose associated with CT scans, much attention is focused on CT protocol review and improvement. In fact, annual protocol reviews will soon be required for ACR CT accreditation. A major challenge in the protocol review process is determining whether a current protocol is optimal and deciding what steps to take to improve it. In this paper, the authors describe methods for pinpointing deficiencies in CT protocols and provide a systematic approach for optimizing them. Emphasis is placed on a team approach, with a team consisting of at least one radiologist, one physicist, and one technologist. This core team completes a critical review of all aspects of a CT protocol and carefully evaluates proposed improvements. Changes to protocols are implemented only with consensus of the core team, with consideration of all aspects of the CT examination, including image quality, radiation dose, patient care and safety, and workflow.

Standardization and Optimization of CT Protocols to Achieve Low Dose

The increase in radiation exposure due to CT scans has been of growing concern in recent years. CT scanners differ in their capabilities, and various indications require unique protocols, but there remains room for standardization and optimization. In this paper, the authors summarize approaches to reduce dose, as discussed in lectures constituting the first session of the 2013 UCSF Virtual Symposium on Radiation Safety and Computed Tomography. The experience of scanning at low dose in different body regions, for both diagnostic and interventional CT procedures, is addressed. An essential primary step is justifying the medical need for each scan. General guiding principles for reducing dose include tailoring a scan to a patient, minimizing scan length, use of tube current modulation and minimizing tube current, minimizing tube potential, iterative reconstruction, and periodic review of CT studies. Organized efforts for standardization have been spearheaded by professional societies such as the American Association of Physicists in Medicine. Finally, all team members should demonstrate an awareness of the importance of minimizing dose.

Optimization of cone beam CT protocols used in image guided radiotherapy applications

Optimization of cone beam CT protocols used in image guided radiotherapy applications

JOURNAL CLUB: CT Dose Optimization for Whole-Body PET/CT Examinations

OBJECTIVE. The objective of this study was to optimize CT protocols for whole-body PET/CT by reducing radiation dose while minimizing effects on image quality. MATERIALS AND METHODS. Before protocol optimization, a survey of 140 consecutive patients was conducted to establish the baseline dose from a whole-body PET/CT examination. Another sample of 100 patients was surveyed to evaluate the reduction of radiation dose after implementation of the new protocol. Effective dose from the CT component of the examination was estimated using dose-length product (DLP) values from reports generated by the scanner and anatomy-specific conversion factors. Twenty-six patients who underwent studies before and after the optimization were included in an analysis of image quality. All 26 patients had maintained the same weight between the examinations and were scanned in the same position using a similar technique except for the changes made for CT dose optimization. The studies were randomized and blinded for an experienced PET and CT reader who graded the imaging quality of anatomic structures. RESULTS. CT protocol optimization resulted in a 32% reduction of the mean CT radiation dose: The mean effective dose was reduced from 8.1 to 5.5 mSv. The blinded analysis of image quality showed no clinically significant degradation of the lower-dose studies. The only structures visualized statistically better on the higher-dose CT scans were the carotid arteries and the region of the posterior triangle. CONCLUSION. The results of this study showed that optimization of CT acquisition can effectively reduce radiation dose in a whole-body PET/CT examination without significantly sacrificing image quality.

SU‐E‐I‐56: An Overview of a CT Protocol Optimization Process at a Major University Hospital Medical Center; Including Details On Physics Support, IT Support, and a Radiologist Based Quality Assurance Program

Purpose: Modern CT departments with multiple scanner architectures can easily have hundreds of different protocols for different size patients and clinical requirements. Unless a systematic approach is taken to the optimization and quality assurance of these protocols, care to the patient in the form of image quality, dose, and clinical usability of the CT exams can be compromised. The purpose of this study is to present the model that has been put into a operational form after being organically developed by the medical physicists, radiologists, IT staff, and CT technologists at our over the last several years. Methods: The process of CT protocol formation will be covered including: assessment of the CT scanner technology by the medical physicist, clinical protocol requirements determined by clinicians, optimization of protocols parameters by the medical physicist, final review of the protocols by the entire protocol optimization team, and the subsequent clinical application of the protocols. After implementation, a clinical quality assurance program enables radiologists to score CT exams while reading them on a standard PACS workstation and concurrently the medical physics team monitors the radiation dose (patient size specific) and reviews image quality concerns made by radiologists. The IT infrastructure for this QA assurance process will also be presented. Results: We have successfully gone through several iterations of the CT protocol optimization procedure presented in this study at our institution. The incorporation of new technologies was reviewed and fit into our protocol optimization process as well. The operational procedures defined in this study have greatly increased the efficiency with which we manage and optimize protocols at our institution. Conclusion: CT protocol optimization is an ongoing process; constant monitoring of patient dose and image quality, incorporation of new scanner technologies, and changing clinical requirements all necessitate an organized approach to CT protocols optimization. Equipment grant from GE healthcare.

WE‐C‐103‐04: The Optimization of CT Protocols Using Plots of CTDIvol and of Max and Min MA Versus Patient Size for Actual Clinical Scans Using Automatic Exposure Control (AEC)

Purpose: To determine the usefulness of the knowledge of CTDIvol and mA variations as a function of patient size for optimizing scan parameters in CT imaging using AEC. Methods: Data was collected from actual patient scans for a number of different CT protocols such as standard chest, body, head, vascular imaging, and pediatric body. A GE LightSpeed VCT scanner was used in Smart mA mode in which the user can select the Noise Index, and the maximum and minimum mA allowed during mA modulation. For each different protocol the CTDIvol, minimum mA, maximum mA and patient size where determined for at least 40 patients, along with information on when the mA had reached its specified minimum or maximum value. Plots were made of the CTDIvol versus patient size and of the maximum and minimum mA versus patient size. Results: Initial results demonstrated a significant variation in CTDIvol over the range of adult patient sizes of more than a factor of ten for abdominal imaging. The observation that clinical scans frequently reached the minimum allowed mA indicated that reduction of the rotation time and lowering of the minimum mA parameter would allow lower patient dose and better operation of the AEC system. These results also led us to create separate protocols for small, medium, and large patients, each with a different optimized Noise Index, kV, rotation time, and mA range. These were created in consultation with our radiologists in determining the lowest dose that would provide a clinically acceptable image after the AEC was deemed to be operating optimally. Conclusion: The above analysis can provide significant help in improving CT protocols and lowering patient dose. The plots of CTDIvol versus patient size also helped to educate radiologists in the dose variations to be expected for a range of patient sizes. Equipment grant from GE healthcare.

TH‐C‐134‐01: Computed Tomography 2: Dose Basics and Getting the Most From Your Dose

TH‐C‐134‐01: Computed Tomography 2: Dose Basics and Getting the Most From Your Dose

Organ individualized dose computing in CT

Introduction The medical imaging becomes the most important ionizing exposure source, made by human, for population. Its dose estimation, especially in computed tomography, is inaccurate because it does not match exactly the patient morphology. That's why it is necessary to realize an individualized dose computing method. The individualized dose results will be obtained thanks to deformable anthropomorphic phantoms and to a dose computing tool previously validated. Material and methods Mathematical phantoms are segmented from real tests in 3 mm sized voxels. These images are converted into DICOM format files with a Matlab ® program and they are now readable by the dose simulation software (ImpactMC, CT Imaging GmbH). Five test types are simulated (brain, thorax, abdomen, pelvis, thoraco-abdo-pelvis). Dose results are finally treated into Matlab ® in order to get the organ dose repartition. Results Computed organ doses will be compared to those obtained with classical methods (CTDosimetry, ImpactDose, CT-Expo, etc.). The influence of patient morphology and the influence of test conditions on the computed doses will be carried out. The method uncertainty will be evaluated, especially the uncertainty which is due to the choice of Hounsfield units attribution to the organs. Conclusion The semi-automatically method of organ dose computing is adapted to the test conditions and to the patient morphology. It will be useful for the dose optimization of CT protocols and for the patient dose estimation for clinical and epidemiological applications. This method can be easily extended to the interventional imaging (angio 3D) or to the radiotherapy imaging (Cone-BeamCT).

SU‐C‐134‐05: CT Contrast Media: Impact of Scanner Parameters On Enhancement and Detectability

Purpose: Uptake of iodine‐based CT contrast media (CM) results in an increase in Hounsfield Unit (HU) value, allowing for improved detectability in CT. Further, because the increase in HU is proportional to CM concentration, quantitative measurement of HU enhancement can aid diagnosis and can determine hemodynamic properties of tissues (i.e., perfusion CT). Imaging protocol parameters (e.g., reconstruction kernel) can alter the HU‐CM relationship, potentially confounding quantitation of contrast uptake. This phantom study measures the HU‐CM relationship and determines the impact of imaging protocol parameters. Methods: A solid water phantom was imaged with a Philips Big Bore CT Scanner. Eighteen custom cylinders with CM concentrations ranging from 0–50 mg of iodine/mL were placed in the phantom. Tube voltages of 90, 120, and 140kVp, current‐time products of 100 and 400mAs, and reconstruction kernels of UB (smooth) and D (hi‐res bone enhancing) were studied. A linear fit to the HU‐CM data was calculated to evaluate HU enhancement. Contrast‐to‐noise ratio (CNR) was calculated to evaluate detectability. Results: A linear relationship existed between HU and CM for all acquisitions (R‐squared > 0.99). HU‐CM linear slope ranged from 16 to 34 HU/mg‐I/mL. A tube voltage of 140kVp increased the slope by 81% when compared to 90kVp, whereas 120kVp increased the slope by 20%. Kernel D produced a 10‐15% increase in slope. For a 400mAs acquisition, CNR was optimized using 120kVp and the UB kernel, but CNR was optimized for 100mAs using 90kVp with the UB kernel. Conclusion: HU enhancement is linear with concentration; however, the slope is strongly impacted by reconstruction kernel and tube voltage. Knowledge of CT scanning parameter impact on contrast media signal enhancement and detectability can guide optimization of CT protocols and improve interpretation of quantitative CT data.

TU‐A‐217BCD‐02: The Role of Physics in CT Protocol Optimization Over the Range of CT Scanner Types: Recommendations and Misconceptions

The understanding of how scan and reconstructions parameters affect image quality, patient dose, and total scan time is essential to the proper optimization of CT scanner protocols. This understanding is greatly complicated by the differences in user interfaces and in the effects of varying scan and reconstruction parameter with scanners from different manufacturers and even with different scanners from the same manufacturer. Certain scan parameters affect patient dose and image quality (kV, mA, rotation time, effective mAs, pitch, noise index (NI), standard deviation, target effective (TE) mAs), while a subset of these affect the total scan time — which is important for breath hold and contrast considerations. There is a logical method of approaching the modifications of these parameters to achieve the necessary diagnostic image quality at the lowest dose, within total scan time limitations. This method must take into account the model and manufacture of CT scanner, but unfortunately has often not been followed in the development of published CT protocols.Some examples of common confusions and misconceptions involving protocol optimization:The automatic exposure control (AEC) systems from various manufacturers have dramatically different interfaces and perform their functions very differently. Even with the use of AEC, optimal CT scans are not usually obtained with a single protocol for all size patients. In AEC mode the dose can be reduced by raising the NI or lowering the TE mAs. However raising the kV can either raise or lower the dose depending on the AEC system used. Imaging infants to large adults can utilize a range of kV from 80 to 140 kV, with large patients requiring a higher NI and lower TE mAs when using AEC.The effects of pitch and the ways to adjust pitch to optimize image quality and patient dose have appeared to be particularly confusing. Raising the pitch above a value of 1.0 is usually not an optimal way to lower dose due to detrimental effects on image artifacts and slice thickness. Instead, the use of a pitch less than 1.0, with shorter rotation times and lower mA is preferred. Pitch values less than 1.0 do not unnecessarily over‐irradiate the patient since the added radiation is effectively utilized in the image reconstruction in reducing image noise. Raising the pitch above 1.0 should be a final step used to reduce the total scan time when it is clinically too long.Learning Objectives:1. Understand the differences in scans and reconstructions parameters between different scanners and the ways in which these parameters affect image quality, patient dose, and total scan time.2. Understand how AEC is used for different CT scanners included its different effects with varying patient size.3. Understand some of the misconceptions involving CT parameters including the role of AEC and pitch in image quality, patient dose, and total scan time.4. Understand the basic principles of CT protocol optimization and how they are affected by scanner type and patient size.

Influence of exposure parameters on patient dose and image noise in computed tomography

Influence of exposure parameters on patient dose and image noise in computed tomography This work presents the results of investigation of influence of main exposure parameters on the patient dose and image noise on five clinical computed tomography units. Patient dose was determined by means of the quantity CTDIair free on air measured with pencil shaped ionization chamber. The image noise was estimated as a standard deviation of CT numbers in a 500 mm2 central region of interest in a water-equivalent phantom positioned in the centre of rotation. The alteration of tube voltage and tube current show the potential in patient dose reduction up to 40% but may deteriorate image quality and has to be carefully applied in order to optimize the clinical CT protocols taking into account the specific clinical task. This survey is essential for optimization of routine CT protocols especially for CT units without automatic exposure control systems, which are main part of CT units in Bulgaria.